In this letter, an enhanced detection scheme using threshold and lattice-reduction algorithm is proposed. The first step of the proposed detection scheme finds another basis channel matrix H' which has good properties from the channel matrix H by using lattice-reduction algorithm. And QRD-M detection scheme using threshold algorithm is executed in the next step. Simulation results show that the proposed method has better performance than the conventional QRD-M detection scheme at high SNR. Also, it reduces candidate symbols because of the threshold algorithm.

Information-theoretic limits of a multi-way relay channel with direct links (MWRC-DL), where multiple users exchange their messages through a relay terminal and direct links, are discussed in this paper. Under the assumption that a restricted encoder is employed at each user, an outer bound on the capacity region is derived first. Then, a decode-and-forward (DF) strategy is proposed and the corresponding rate region is characterized. The explicit outer bound and the achievable rate region for the Gaussian MWRC-DL are also derived. Numerical examples are provided to demonstrate the performance of the proposed DF strategy.

This paper presents the effect of transmit diversity on the initial and neighboring cell search time performance and the most appropriate transmit diversity scheme based on system-level simulations employing synchronization signals for the Long Term Evolution (LTE) downlink. The synchronization signals including the primary synchronization signal (PSS) and secondary synchronization signal (SSS) are the first physical channel that a set of user equipment (UE) acquires at the initial radio-link connection. The transmit diversity candidates assumed in the paper are Precoding Vector Switching (PVS), Cyclic Delay Diversity (CDD), Time Switched Transmit Diversity (TSTD), and Frequency Switched Transmit Diversity (FSTD), which are all suitable for simple blind detection at a UE. System-level simulation results show that transmit diversity is effective in improving the detection probabilities of the received PSS timing and PSS sequence in the first step and those of the SSS sequence and radio frame timing in the second step of the cell search process. We also show that PVS achieves fast cell search time performance of less than approximately 20ms at the location probability of 90% regardless of the inter-cell site distance up to 10km. Hence, we conclude that PVS is the best transmit diversity scheme for the synchronization signals from the viewpoint of decreasing the initial and neighboring cell search times.

A hinge vertex is a vertex in an undirected graph such that there exist two vertices whose removal makes the distance between them longer than before. Identifying hinge vertices in a graph can help detect critical nodes in communication network systems, which is useful for making them more stable. For finding them, an O(n3) time algorithm was developed for a simple graph, and, linear time algorithms were developed for interval and permutation graphs, respectively. Recently, the maximum detour hinge vertex problem is defined by Honma et al. For a hinge vertex u in a graph, the detour degree of u is the largest value of distance between any pair of x and y (x and y are adjacent to u) by removing u. A hinge vertex with the largest detour degree in G is defined as the maximum detour hinge vertex of G. This problem is motivated by practical applications, such as network stabilization with a limited cost, i.e., by enhancing the reliability of the maximum detour hinge vertex, the stability of the network is much improved. We previously developed an O(n2) time algorithm for solving this problem on an interval graph. In this study, we propose an algorithm that identifies the maximum detour hinge vertex on a permutation graph in O(n2) time, where n is the number of vertices in the graph.

In this letter, we present an authentication and recovery scheme to protect images. The image blocks are DCT transformed and then encoded with different patterns. An optimal selection is adopted to find the best pattern for each block which results in better image quality. Both the recovery and check data are embedded for data protection. The experimental results demonstrate that our method is able to identify and localize regions having been tampered with. Furthermore, good image quality for both watermarked and recovered images are effectively preserved.

A renal biopsy is a procedure to get a small piece of kidney for microscopic examination. With the development of tissue sectioning and medical imaging techniques, microscope renal biopsy image sequences are consequently obtained for computer-aided diagnosis. This paper proposes a new context-based segmentation algorithm for acquired image sequence, in which an improved genetic algorithm (GA) patching method is developed to segment different size target. To guarantee the correctness of first image segmentation and facilitate the use of context information, a boundary fusion operation and a simplified scale-invariant feature transform (SIFT)-based registration are presented respectively. The experimental results show the proposed segmentation algorithm is effective and accurate for renal biopsy image sequence.

In this paper, we propose a zero-forcing (ZF) Tomlinson-Harashima precoding (THP) with substream permutations based on the bit rate maximization for single-user MIMO (SU-MIMO) systems. We study the effect of substream permutations on the ZF-THP SU-MIMO systems, when the mean squared error (MSE) and the bit rate are adopted for the selection of the permutation matrix as criteria. Based on our analysis, we propose a method to increase the bit rate by substream permutations, and derive QR and Cholesky decomposition-based algorithms which realize the proposed method. Furthermore, to improve the error rate performance, we apply zero transmission to subchannels with low signal-to-noise ratios. Numerical examples are provided to demonstrate the effectiveness of the proposed THP MIMO system.

Developing a practical and accurate statistical parser for low-resourced languages is a hard problem, because it requires large-scale treebanks, which are expensive and labor-intensive to build from scratch. Unsupervised grammar induction theoretically offers a way to overcome this hurdle by learning hidden syntactic structures from raw text automatically. The accuracy of grammar induction is still impractically low because frequent collocations of non-linguistically associable units are commonly found, resulting in dependency attachment errors. We introduce a novel approach to building a statistical parser for low-resourced languages by using language parameters as a guide for grammar induction. The intuition of this paper is: most dependency attachment errors are frequently used word orders which can be captured by a small prescribed set of linguistic constraints, while the rest of the language can be learned statistically by grammar induction. We then show that covering the most frequent grammar rules via our language parameters has a strong impact on the parsing accuracy in 12 languages.

Recently, the ratio of probability density functions was demonstrated to be useful in solving various machine learning tasks such as outlier detection, non-stationarity adaptation, feature selection, and clustering. The key idea of this density ratio approach is that the ratio is directly estimated so that difficult density estimation is avoided. So far, parametric and non-parametric direct density ratio estimators with various loss functions have been developed, and the kernel least-squares method was demonstrated to be highly useful both in terms of accuracy and computational efficiency. On the other hand, recent study in pattern recognition exhibited that deep architectures such as a convolutional neural network can significantly outperform kernel methods. In this paper, we propose to use the convolutional neural network in density ratio estimation, and experimentally show that the proposed method tends to outperform the kernel-based method in outlying image detection.

We investigate the origin of non-ideal transfer characteristics in graphene-based three-branch nano-junction (TBJ) devices. Fabricated graphene TBJs often show asymmetric nonlinear voltage transfer characteristic, although symmetric one should appear ideally. A simple model considering the contact resistances in two input electrodes is deduced and it suggests that the non-ideal characteristic arises from inequality of the metal-graphene contact resistances in the inputs. We fabricate a graphene TBJ device with electrically equal contacts by optimizing the contact formation process and almost ideal nonlinear characteristic was successfully demonstrated.

To ensure the security of image transmission, this paper presents a new image encryption algorithm based on a genetic algorithm (GA) and a piecewise linear chaotic map (PWLCM), which adopts the classical diffusion-substitution architecture. The GA is used to identify and output the optimal encrypted image that has the highest entropy value, the lowest correlation coefficient among adjacent pixels and the strongest ability to resist differential attack. The PWLCM is used to scramble pixel positions and change pixel values. Experiments and analyses show that the new algorithm possesses a large key space and resists brute-force, statistical and differential attacks. Meanwhile, the comparative analysis also indicates the superiority of our proposed algorithm over a similar, recently published, algorithm.

Recently, we proposed an interference-aware channel segregation based dynamic channel assignment (IACS-DCA). In IACS-DCA, each base station (BS) measures the instantaneous co-channel interference (CCI) power on each available channel, computes the moving average CCI power using past CCI measurement results, and selects the channel having the lowest moving average CCI power. In this way, the CCI-minimized channel reuse pattern can be formed. In this paper, we introduce the autocorrelation function of channel reuse pattern, the fairness of channel reuse, and the minimum co-channel BS distance to quantitatively examine the channel reuse pattern formed by the IACS-DCA. It is shown that the IACS-DCA can form a CCI-minimized channel reuse pattern in a distributed manner and that it improves the signal-to-interference ratio (SIR) compared to the other channel assignment schemes.

Controlling interference from the secondary system (SS) to the receiver of the primary system (PS) is an important issue when the SS uses the same frequency band as the television broadcast system. The reason includes that the SS is unaware of the interference imposed on the primary receiver (PS-Rx), which does not have a transmitter. In this paper, we propose an interference control method between PS-Rx and SS, where a load modulation scheme is introduced to the PS-Rx. In this method, the signal from the PS transmitting station is scattered by switching its load impedance. The SS observes the scattered channel and calculates the interference suppression weights for transmitting, and controls interference by transmit beamforming. A simulation shows that the Signal-to-Interference Ratio (SIR) with interference control is improved by up to 41.5dB compared to that without interference control at short distances; the results confirm that the proposed method is effective in controlling interference between PS-Rx and SS. Furthermore, we evaluate the Signal-to-Noise Ratio (SNR) and channel capacity at SS.

We have demonstrated tunable extit{n}-channel fullerene and extit{p}-channel pentacene OFETs and CMOS inverter circuit based on a bilayer-dielectric structure of CYTOP (poly(perfluoroalkenyl vinyl ether)) electret and SiO$_{2}$. For both OFET types, the $V_{mathrm{th}}$ can be electrically tuned thanks to the charge-trapping at the interface of CYTOP and SiO$_{2}$. The stability of the shifted $V_{mathrm{th}}$ was investigated through monitoring a change in transistor current. The measured transistor current versus time after programming fitted very well with a stretched-exponential distribution with a long time constant up to 10$^{6}$ s. For organic CMOS inverter, after applying the program gate voltages for extit{n}-channel fullerene or extit{p}-channel pentacene elements, the voltage transfer characteristics were shifted toward more positive values, resulting in a modulation of the noise margin. We realized that at a program gate voltage of 60,V for extit{p}-channel OFET, the circuit switched at 4, 8,V, that is close to half supply voltage $V_{mathrm{DD}}$, leading to the maximum electrical noise immunity of the inverter circuit.

Robust crater recognition is a research focus on deep space exploration mission, and sparse representation methods can achieve desirable robustness and accuracy. Due to destruction and noise incurred by complex topography and varied illumination in planetary images, a robust crater recognition approach is proposed based on dictionary learning with a low-rank error correction model in a sparse representation framework. In this approach, all the training images are learned as a compact and discriminative dictionary. A low-rank error correction term is introduced into the dictionary learning to deal with gross error and corruption. Experimental results on crater images show that the proposed method achieves competitive performance in both recognition accuracy and efficiency.

Fast simulation techniques of large scale RLC networks with nonlinear devices are presented. Generally, when scale of nonlinear part in a circuit is much less than the linear part, matrix or circuit partitioning approach is known to be efficient. In this paper, these partitioning techniques are used for the conventional transient analysis using an implicit numerical integration and the circuit-based finite-difference time-domain (FDTD) method, whose efficiency and accuracy are evaluated developing a prototype simulator. It is confirmed that the matrix and circuit partitioning approaches do not degrade accuracy of the transient simulations that is compatible to SPICE, and that the circuit partitioning approach is superior to the matrix one in efficiency. Moreover, it is demonstrated that the circuit-based FDTD method can be efficiently combined with the matrix or circuit partitioning approach, compared with the transient analysis using an implicit numerical integration.

Millimeter-wave (mm-wave) radio is attracting attention as one of the key enabling physical layer technologies for the fifth-generation (5G) mobile access and backhaul. This paper aims at clarifying possible roles of mm-wave radio in the 5G development and performing a comprehensive literature survey on mm-wave radio channel modeling essential for the feasibility study. Emphasis in the literature survey is laid on grasping the typical behavior of mm-wave channels, identifying missing features in the presently available channel models for the design and evaluation of the mm-wave radio links within the 5G context, and exemplifying different channel modeling activities through analyses performed in the authors' group. As a key technological element of the mm-wave radios, reduced complexity beamforming is also addressed. Design criteria of the beamforming are developed based on the spatial multipath characteristics of measured indoor mm-wave channels.

Gallium oxide is expected as a channel material for thin film transistors. In the conventional technologies, gallium oxide has been tried to be fabricated by atomic layer deposition (ALD) at high temperatures from 100--450$^{circ}$C, although the room-temperature (RT) growth has not been developed. In this work, we developed the RT ALD of gallium oxide by using a remote plasma technique. We studied trimethylgallium (TMG) adsorption and its oxidization on gallium oxide surfaces at RT by infrared absorption spectroscopy (IRAS). Based on the adsorption and oxidization characteristics, we designed the room temperature ALD of Ga$_{2}$O$_{3}$. The IRAS indicated that TMG adsorbs on the gallium oxide surface by consuming the adsorption sites of surface hydroxyl groups even at RT and the remote plasma-excited water and oxygen vapor is effective in oxidizing the TMG adsorbed surface and regeneration of the adsorption sites for TMG. We successfully prepared Ga$_{2}$O$_{3}$ films on Si substrates at RT with a growth per cycle of 0.055,nm/cycle.

The capacity maximization of line-of-sight (LoS) two-input and multiple-output (TIMO) channels in indoor environments is investigated in this paper. The 3×2 TIMO channel is mainly studied. First, the capacity fluctuation number (CFN) which reflects the variation of channel capacity is proposed. Then, the expression of the average capacity against the CFN is derived. The CFN is used as a criterion for optimization of the capacity by changing inter-element spacings of transmit and receive antenna arrays. Next, the capacity sensitivity of the 3×2 TIMO channel to the orientation and the frequency variation is studied and compared with those of 2×2 and 4×2 TIMO channels. A small capacity sensitivity of the 3×2 TIMO channel is achieved and verified by both simulation and measurement results. Furthermore, the CFN can also be used as a criterion for optimization of average capacity and the proposed optimization method is validated through numerical results.

Topic features are useful in improving text summarization. However, independency among topics is a strong restriction on most topic models, and alleviating this restriction can deeply capture text structure. This paper proposes a hybrid topic model to generate multi-document summaries using a combination of the Hidden Topic Markov Model (HTMM), the surface texture model and the topic transition model. Based on the topic transition model, regular topic transition probability is used during generating summary. This approach eliminates the topic independence assumption in the Latent Dirichlet Allocation (LDA) model. Meanwhile, the results of experiments show the advantage of the combination of the three kinds of models. This paper includes alleviating topic independency, and integrating surface texture and shallow semantic in documents to improve summarization. In short, this paper attempts to realize an advanced summarization system.