The effects of the gate dielectrics on ambipolar transport in top-gate-type polymer light-emitting transistors with single-layer and bilayer gate dielectrics are investigated. Hole field-effect mobility is dependent on the dielectric constant of the gate dielectric onto the active layer. Hole transport of devices is affected by the dipolar disorder in the first gate dielectric layer on the active layer. Electron threshold voltage tends to decrease with increasing the total stacked gate capacitance.

A transmission ellipsometric method without an aperture was recently developed to characterize the electro-optic (EO) performance of EO polymers. The method permits much simpler optical setup compared to the reflection method, and allows easy performance of the incident angle dependence measurements using a conventional glass substrate and uncollimated beam. This paper shows the usefulness of this method for a simple and reliable evaluation of the EO coefficient both for organic and inorganic EO materials, as well as analysis for uniaxial anisotropic materials.

Coarse Grained Reconfigurable Architectures (CGRAs) are promising platform based on its high-performance and low cost. Researchers have developed efficient compilers for mapping compute-intensive applications on CGRA using modulo scheduling. In order to generate loop kernel, every stage of kernel are forced to have the same execution time which is determined by the critical PE. Hence non-critical PEs can decrease the supply voltage according to its slack time. The variable Dual-VDD CGRA incorporates this feature to reduce power consumption. Previous work mainly focuses on calculating a global optimal VDDL using overall optimization method that does not fully exploit the flexibility of architecture. In this brief, we adopt variable optimal VDDL in each stage of kernel concerning their pattern respectively instead of the fixed simulated global optimal VDDL. Experiment shows our proposed heuristic approach could reduce the power by 27.6% on average without decreasing performance. The compilation time is also acceptable.

In this article we present a novel corpus-based method for inducing romanization systems for languages through a bilingual alignment of transliteration word pairs. First, the word pairs are aligned using a non-parametric Bayesian approach, and then for each grapheme sequence to be romanized, a particular romanization is selected according to a user-specified criterion. As far as we are aware, this paper is the only one to describe a method for automatically deriving complete romanization systems. Unlike existing human-derived romanization systems, the proposed method is able to discover induced romanization systems tailored for specific purposes, for example, for use in data mining, or efficient user input methods. Our experiments study the romanization of four totally different languages: Russian, Japanese, Hindi and Myanmar. The first two languages already have standard romanization systems in regular use, Hindi has a large number of diverse systems, and Myanmar has no standard system for romanization. We compare our induced romanization system to existing systems for Russian and Japanese. We find that the systems so induced are almost identical to Russian, and 69% identical to Japanese. We applied our approach to the task of transliteration mining, and used Levenshtein distance as the romanization selection criterion. Our experiments show that our induced romanization system was able to match the performance of the human created system for Russian, and offer substantially improved mining performance for Japanese. We provide an analysis of the mechanism our approach uses to improve mining performance, and also analyse the differences in characteristics between the induced system for Japanese and the official Japanese Nihon-shiki system. In order to investigate the limits of our approach, we studied the romanization of Myanmar, a low-resource language with a large vocabulary of graphemes. We estimate the approximate corpus size required to effectively romanize the most frequency k graphemes in the language for all values of k up to 1800.

We present an algorithm for efficient rendering of animated hair under a dynamic, low-frequency lighting environment. We use spherical harmonics (SH) to represent the environmental light. The transmittances between a point on a hair strand and the light sources are also represented by SH functions. Then, a convolution of SH functions and the scattering function of a hair strand is precomputed. This allows us to efficiently compute the intensity at a point on the hair. However, the computation of the transmittance is very time-consuming. We address this problem by using a voxel-based approach: the transmittance is computed by using a voxelized hair model. We further accelerate the computation by sampling the voxels. By using our method, we can render a hair model consisting of tens of thousands of hair strands at interactive frame rates.

Modularity is an effective evaluation approach for understanding the structural quality of evolutionary software. However, there are many diverse ways to measure it. In this paper, we analyze and compare various modularity metrics that have been studied in different domains to assess their applicability to evolutionary software analysis. Through extensive experiments with artificial DSMs and open-source software, we find that the correlations of those metrics are generally high despite their differences. However, our experiments show that a certain metric can be more sensitive to particular modular factors, hence applying of comprehensive modularity metrics must be taken into consideration.

This paper proposes a graph-theory-based Euler number computing algorithm. According to the graph theory and the analysis of a mask's configuration, the Euler number of a binary image in our algorithm is calculated by counting four patterns of the mask. Unlike most conventional Euler number computing algorithms, we do not need to do any processing of the background pixels. Experimental results demonstrated that our algorithm is much more efficient than conventional Euler number computing algorithms.

We consider user selection schemes for multi-user MIMO systems with linear precoding. In this work, we apply two user selection schemes based on the orthogonality between the propagation channel of MSs. Indoor transmission experiments are carried out under several scenarios and the performances of user selection schemes are evaluated. It is shown that the transmission performance is improved and the user selection schemes are remarkably affected by the path loss between MSs.

The success of heuristic search in AI planning largely depends on the design of the heuristic. On the other hand, previous experience contains potential domain information that can assist the planning process. In this context, we have studied dynamic macro-based heuristic planning through action relationship analysis. We present an approach for analyzing the action relationship and design an algorithm that learns macros in solved cases. We then propose a dynamic macro-based heuristic that appropriately reuses the macros rather than immediately assigning them to domains. The above ideas are incorporated into a working planning system called Dynamic Macro-based Fast Forward planner. Finally, we evaluate our method in a series of experiments. Our method effectively optimizes planning since it reduces the result length by an average of 10% relative to the FF, in a time-economic manner. The efficiency is especially improved when invoking an action consumes time.

This paper investigates the system-level throughput of non-orthogonal multiple access (NOMA) with a successive interference canceller (SIC) in the cellular downlink assuming proportional fair (PF)-based radio resource (bandwidth and transmission power) allocation. The purpose of this study is to examine the possibility of applying NOMA with a SIC to the systems beyond the 4G cellular system. Both the mean and cell-edge user throughput are important in a real system. PF-based scheduling is known to achieve a good tradeoff between them by maximizing the product of the user throughput among users within a cell. In NOMA with a SIC, the scheduler allocates the same frequency to multiple users simultaneously, which necessitates multiuser scheduling. To achieve a better tradeoff between the mean and cell-edge user throughput, we propose and compare three power allocation strategies among users, which are jointly implemented with multiuser scheduling. Extensive simulation results show that NOMA with a SIC with a moderate number of non-orthogonally multiplexed users significantly enhances the system-level throughput performance compared to orthogonal multiple access (OMA), which is widely used in 3.9 and 4G mobile communication systems.

Video Up-scaling is a hotspot in TV display area; as an important brunch of Video Up-scaling, Texture-Based Video Up-scaling (TBVU) method shows great potential of hardware implementation. Coarse-grained Reconfigurable Architecture (CGRA) is a very promising processor; it is a parallel computing platform which provides high performance of hardware, high flexibility of software, and dynamical reconfiguration ability. In this paper we propose an implementation of TBVU on CGRA. We fully exploit the characters of TBVU and utilize several techniques to reduce memory I/O operation and total execution time. Experimental results show that our work can greatly reduce the I/O operation and the execution time compared with the non-optimized ones. We also compare our work with other platforms and find great advantage in execution time and resource utilization rate.

In this paper, we discuss performance modeling of 3-D stencil computing on an FPGA accelerator with a high-level synthesis environment, aiming for efficient exploration of user-space design parameters. First, we analyze resource utilization and performance to formulate these relationships as mathematical models. Then, in order to evaluate our proposed models, we implement heat conduction simulations as a benchmark application, by using MaxCompiler, which is a high-level synthesis tool for FPGAs, and MaxGenFD, which is a domain specific framework of the MaxCompiler for finite-difference equation solvers. The experimental results with various settings of architectural design parameters show the best combination of design parameters for pipeline structure can be systematically found by using our models. The effects of changing arithmetic accuracy and using data stream compression are also discussed.

In this paper, optimal control of multi-vehicle systems is studied. In the case where collision avoidance between vehicles and obstacle avoidance are imposed, state discretization is effective as one of the simplified approaches. Furthermore, using state discretization, cooperative actions such as rendezvous can be easily specified by linear temporal logic (LTL) formulas. However, it is not necessary to discretize all states, and partial states (e.g., the position of vehicles) should be discretized. From this viewpoint, a new control method for multi-vehicle systems is proposed in this paper. First, the system in which partial states are discretized is formulated. Next, the optimal control problem with constraints described by LTL formulas is formulated, and its solution method is proposed. Finally, numerical simulations are presented. The proposed method provides us a useful method in control of multi-vehicle systems.

A processing system with multiple field programmable gate array (FPGA) cards is described. Each FPGA card can interconnect using six I/O (up, down, left, right, front, and back) terminals. The communication network among FPGAs is scalable according to user design. When the system operates multi-dimensional applications, transmission efficiency among FPGA improved through user-adjusted dimensionality and network topologies for different applications. We provide a fast and flexible circuit configuration method for FPGAs of a multi-dimensional FPGA array. To demonstrate the effectiveness of the proposed method, we assess performance and power consumption of a circuit that calculated 3D Poisson equations using the finite difference method.

This paper presents an analog front-end circuit for a 60-GHz proximity wireless communication receiver. The feature of the proposed analog front-end circuit is a bandwidth more than 1-GHz wide. To expand the bandwidth of a low-pass filter and a voltage gain amplifier, a technique to reduce the parasitic capacitance of a transconductance amplifier is proposed. Since the bandwidth is also limited by on-resistance of the ADC sampling switch, a switch separation technique for reduction of the on-resistance is also proposed. In a high-speed ADC, the SNDR is limited by the sampling jitter. The developed high resolution VCO auto tuning effectively reduces the jitter of PLL. The prototype is fabricated in 65nm CMOS. The analog front-end circuit achieves over 1-GHz bandwidth and 27.2-dB SNDR with 224mW Power consumption.

In this paper, we modify the Legendre-Sidelnikov sequence which was defined by M. Su and A. Winterhof and consider its exact autocorrelation values. This new sequence is balanced for any p,q and proved to possess low autocorrelation values in most cases.

For low-density parity-check codes, spatial coupling was proved to boost the performance of iterative decoding up to the optimal performance. As an application of spatial coupling, in this paper, bit-interleaved coded modulation (BICM) with spatially coupled (SC) interleaving — called SC-BICM — is considered to improve the performance of iterative channel estimation and decoding for block-fading channels. In the iterative receiver, feedback from the soft-in soft-out decoder is utilized to refine the initial channel estimates in linear minimum mean-squared error (LMMSE) channel estimation. Density evolution in the infinite-code-length limit implies that the SC-BICM allows the receiver to attain accurate channel estimates even when the pilot overhead for training is negligibly small. Furthermore, numerical simulations show that the SC-BICM can provide a steeper reduction in bit error rate than conventional BICM, as well as a significant improvement in the so-called waterfall performance for high rate systems.

In this paper, we propose a novel ranking method called VisualTextualRank which ranks media data according to the relevance between the data and specified keywords. We apply our method to the system of video shot ranking which aims to automatically obtain video shots corresponding to given action keywords from Web videos. The keywords can be any type of action such as “surfing wave” (sport action) or “brushing teeth” (daily activity). Top ranked video shots are expected to be relevant to the keywords. While our baseline exploits only visual features of the data, the proposed method employs both textual information (tags) and visual features. Our method is based on random walks over a bipartite graph to integrate visual information of video shots and tag information of Web videos effectively. Note that instead of treating the textual information as an additional feature for shot ranking, we explore the mutual reinforcement between shots and textual information of their corresponding videos to improve shot ranking. We validated our framework on a database which was used by the baseline. Experiments showed that our proposed ranking method, VisualTextualRank, improved significantly the performance of the system of video shot extraction over the baseline.

It is significant to develop better search methods to handle the rapidly increasing volume of multimedia data. For NN (Nearest Neighbor) search in metric spaces, the TLAESA (Tree Linear Approximating and Eliminating Search Algorithm) is a state of art fast search method. In this paper a method is proposed to improve the TLAESA by revising the tree structure with an optimal number of selected global pivots in the higher levels as representatives and employing the best-first search strategy. Based on an improved version of the TLAESA that succeeds in using the best-first search strategy to greatly reduce the distance calculations, this method improves the drawback that calculating less at the price of the lower pruning rate of branches. The lower pruning rate further can lead to lower search efficiency, because the priority queue used in the adopted best-first search strategy stores the information of the visited but unpruned nodes, and need be frequently accessed and sorted. In order to enhance the pruning rate of branches, the improved method tries to make more selected global pivots locate in the higher levels of the search tree as representatives. As more real distances instead of lower bound estimations of the node-representatives are used for approximating the closet node and for “branch and bound”, not only which nodes are close to the query object can be evaluated more effectively, but also the pruning rate of branches can be enhanced. Experiments show that for k-NN queries in Euclidean space, in a proper pivot selection strategy the proposed method can reach the same fewest distance calculations as the LAESA (Linear Approximating and Eliminating Search Algorithm) which saves more calculations than the TLAESA, and can achieve a higher search efficiency than the TLAESA.