In this short correspondence, (1+uv)-constacyclic codes over the finite non-chain ring R[v]/(v2+v) are investigated, where R=F2+uF2 with u2=0. Some structural properties of this class of constacyclic codes are studied. Further, some optimal binary linear codes are obtained from these constacyclic codes.

We propose a quasi-linear trellis-coded modulation (TCM) using nonbinary convolutional codes for quadrature amplitude modulation (QAM). First, we study a matched mapping which is able to reduce the computational complexity of the Euclidean distances between signal points of MQAM. As an example, we search for rate R=1/2 convolutional codes for coded 64QAM by this method. The symbol error rates of the proposed codes are estimated by the distance properties theoretically and they are verified by simulation. In addition, we compare the minimum free Euclidean distances of these new codes with their upper bounds. Finally, the bit error probabilitiy of the proposed coded modulation is compared with uncoded signal constellations and a conventional TCM code proposed by Ungerboeck. The result shows the proposed scheme outperform them on the AWGN channels.

Displacement mapping has been widely used for adding geometric surface details to 3D mesh models. However, it requires sufficient tessellation of the mesh if fine details are to be represented. In this paper, we propose a method for applying the displacement mapping even on coarse models by using an augmented patch mesh. The patch mesh is a regularly tessellated flat square mesh, which is mapped onto the target area. Our method applies displacement mapping to the patch mesh for fitting it to the original mesh as well as for adding surface details. We generate a patch map, which stores three-dimensional displacements from the patch mesh to the original mesh. A displacement map is also provided for defining the new surface feature. The target area in the original mesh is then replaced with the patch mesh, and the patch mesh reconstructs the original shape using the patch map and the new surface detail is added using the displacement map. Our results show that our method conveniently adds surface features to various models. The proposed method is particularly useful if the surface features change dynamically since the original mesh is preserved and the separate patch mesh overwrites the target area at runtime.

Multi-antenna relay transport protocols are analysed, the transmitting matrix of relay node can split into a forward and a backward filters, and these two filters are cascade connection. Based on the zero-forcing relaying protocol, a spatial channel mapping matrix is added between these two filters, and a unified framework of spatial channel mapping matrix is proposed. Then, various linear system designs are summarized, the spatial channel mapping matrix is used to reduce destination noise, so that the relaying noise is suppressed in destination node, and the transmitting power of relay is efficiently utilized. Meanwhile, source node preprocessing operation and destination node equalizer are considered. Simulation results show that the spatial channel mapping matrix has an advantage in terms of system outage probability and capacity performance, and the result is consistent with theoretical analysis.

This paper presents a method to reduce I/O cost in MapReduce when online analytical processing (OLAP) queries are used for data analysis. The proposed method consists of two basic ideas. First, to reduce network transmission cost, mappers are organized to receive only data necessary to perform a map task, not an entire set of input data. Second, to reduce storage consumption, only record IDs are stored for checkpointing, not the raw records. Experiments conducted with TPC-H benchmark show that the proposed method is about 40% faster than Hive, the well-known data warehouse solution for MapReduce, while reducing the size of data stored for checkpoining to about 80%.

In a proxy re-encryption (PRE) scheme, a delegator gives a re-encryption key to a semi-trusted proxy, then the proxy can transform the delegator's ciphertexts into one that can be decrypted by a delegatee who is appointed by the delegator. The proxy cannot, however, learn anything about the encrypted messages. At CCS 2007, Canetti and Hohenberger left an interesting open problem of how to design a PRE scheme that is simultaneously unidirectional and multi-hop. This is a rather interesting problem since in some applications we may need this feature, such as in the scenario of email forwarding, a delegatee wants forward his emails that received from the delegator to another delegatee. In this work we design an unidirectional and multi-hop PRE scheme by using multilinear maps. A shortcoming of our scheme is that its security relies on some rather strong assumptions in the setting of multilinear groups.

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.

Highly accurate pedestrian position information is required in many applications, especially in automatic driving system. Global Positioning System (GPS) developed by American has proven itself reliability in most of the environments. Unfortunately, urban areas contain the signal reflection, known as multipath and non-line-of-sight (NLOS) effects. In addition, the lake of line-of-sight (LOS) satellites caused by the blockage of skyscrapers also severely degrades the accuracy and availability of the GPS positioning. To solve these problems, a solution that interoperated several Global Navigation Satellite Systems (GNSSs) is proposed. However, the actual difficulty of satellite positioning in urban area is the distorted satellite distribution. This paper proposes a GPS with 3D map ray tracing positioning method to conquer the difficulty. The proposed method takes the advantage of the non-LOS (NLOS) and uses it as an additional measurement. Significantly, these measurements are sourced from the satellites that should be blocked. Thus, the dilution of precision (DOP) can be greatly improved. To verify the performance of the proposed method, real data is collected at Tokyo urban area. This paper compares the performance of GPS/GLONASS and the proposed GPS with 3D map ray tracing methods. The results reveals the proposed method is capable of identifying which side of street the pedestrian stands and the GPS+GLONASS method is not.

The MapReduce job scheduler implemented in Hadoop is a mechanism to decide which job is allowed to use idle resources in Hadoop. In terms of the mean job response time, the performance of the job scheduler strongly depends on the job arrival pattern, which includes job size (i.e., the amount of required resources) and their arrival order. Because existing schedulers do not utilize information about job sizes, however, those schedulers suffer severe performance degradation with some arrival patterns. In this paper, we propose a scheduler that estimates and utilizes remaining job sizes, in order to achieve good performance regardless of job arrival patterns. Through simulation experiments, we confirm that for various arrival patterns, the proposed scheduler achieves better performance than the existing schedulers.

The increasing complexity of embedded applications and the prevalence of multiprocessor system-on-chip (MPSoC) introduce a great challenge for designers on how to achieve performance and programmability simultaneously in embedded systems. Automatic multithreaded code generation methods taking account of performance optimization techniques can be an effective solution. In this paper, we consider the issue of increasing processor utilization and reducing communication cost during multithreaded code generation from Simulink models to improve system performance. We propose a combination of three-layered multithreaded software with Integer Linear Programming (ILP) based design-time mapping and scheduling policies to get optimal performance. The hierarchical software with a thread layer increases processor usage, while the mapping and scheduling policies formulate a group of integer linear programming formulations to minimize communication cost as well as to maximize performance. Experimental results demonstrate the advantages of the proposed techniques on performance improvements.

In this paper, we consider distributed estimation where the measurement at each of the distributed sensor nodes is quantized before being transmitted to a fusion node which produces an estimate of the parameter of interest. Since each quantized measurement can be linked to a region where the parameter is found, aggregating the information obtained from multiple nodes corresponds to generating intersections between the regions. Thus, we develop estimation algorithms that seek to find the intersection region with the maximum likelihood rather than the parameter itself. Specifically, we propose two practical techniques that facilitate fast search with significantly reduced complexity and apply the proposed techniques to a system where an acoustic amplitude sensor model is employed at each node for source localization. Our simulation results show that our proposed algorithms achieve good performance with reasonable complexity as compared with the minimum mean squared error (MMSE) and the maximum likelihood (ML) estimators.

This paper presents an efficient method using Hadoop MapReduce for constructing a K-nearest neighbor graph (K-NNG) from a large-scale data set. K-NNG has been utilized as a data structure for data analysis techniques in various applications. If we are to apply the techniques to a large-scale data set, it is desirable that we develop an efficient K-NNG construction method. We focus on NN-Descent, which is a recently proposed method that efficiently constructs an approximate K-NNG. NN-Descent is implemented on a shared-memory system with OpenMP-based parallelization, and its extension for the Hadoop MapReduce framework is implied for a larger data set such that the shared-memory system is difficult to deal with. However, a simple extension for the Hadoop MapReduce framework is impractical since it requires extremely high system performance because of the high memory consumption and the low data transmission efficiency of MapReduce jobs. The proposed method relaxes the requirement by improving the MapReduce jobs, which employs an appropriate key-value pair format and an efficient sampling strategy. Experiments on large-scale data sets demonstrate that the proposed method both works efficiently and is scalable in terms of a data size, the number of machine nodes, and the graph structural parameter K.

This paper studies mapping techniques of multiple applications on embedded many-core SoCs. The mapping techniques proposed in this paper are static which means the mapping is decided at design time. The mapping techniques take into account both inter-application and intra-application parallelism in order to fully utilize the potential parallelism of the many-core architecture. Additionally, the proposed static mapping supports dynamic application switching, which means the applications mapped onto the same cores are switched to each other at runtime. Two approaches are proposed for static mapping: one approach is based on integer linear programming and the other is based on a greedy algorithm. Experimental results show the effectiveness of the proposed techniques.

We consider an improved control method based on the Stability Transformation Method. Stability Transformation Method detects unknown and unstable periodic orbits of chaotic dynamical systems. Based on the approach to realize the Stability Transformation Method in real systems, we have proposed a control method which can stabilize unknown and unstable periodic orbits embedded in chaotic attractors. However, setting of the control parameters of the control system has remained as unsolved issue. When the dynamics of a target system are unknown, the control parameters have to be set by trial and error. In this paper, we improve the control method with the automatic adjustment function of the control parameters. We show an example of stabilizing unstable periodic orbits of the 3-dimensional hysteresis chaos generator by using the proposed control method. Some results are confirmed by laboratory measurements. The results imply that any unknown and unstable periodic orbits can be stabilized by using the proposed method, if the target chaos system is reduced to 1-dimensional return map.

NAND-based block devices such as memory cards and solid-state drives embed a flash translation layer (FTL) to emulate the standard block device interface and its features. The overall performance of these devices is determined mainly by the efficiency of the FTL scheme, so intensive research has been performed to improve the average performance of the FTL scheme. However, its worst-case performance has rarely been considered. The present study aims to improve the worst-case performance without affecting the average performance. The central concept is to distribute the garbage collection cost, which is the main source of performance fluctuations, over multiple requests. The proposed scheme comprises three modules: i) anticipated partial log block merging to distribute the garbage collection time; ii) reclaiming clean pages by moving valid pages to bound the worst-case garbage collection time, instead of performing repeated block merges; and iii) victim selection based on the valid page count in a victim log and the required clean page count to avoid subsequent garbage collections. A trace-driven simulation showed that the worst-case performance was improved up to 1,300% using the proposed garbage collection scheme. The average performance was also similar to that of the original scheme. This improvement was achieved without additional memory overheads.

A global tone mapping operation (TMO) for high dynamic range (HDR) images with fixed-point arithmetic is proposed and evaluated in this paper. A TMO generates a low dynamic range (LDR) image from an HDR image by compressing its dynamic range. Since an HDR image is generally expressed in a floating-point data format, a TMO also deals with floating-point data even though a resultant LDR image is integer data. The proposed method treats a floating-point number as two 8-bit integer numbers which correspond to an exponent part and a mantissa part, and applies tone mapping to these integer numbers separately. Moreover, the method conducts all calculations in the tone mapping with only fixed-point arithmetic. As a result, the method reduces a memory cost and a computational cost. The evaluation shows that the proposed method reduces 81.25% of memory usage. The experimental results show that the processing speed of the proposed method with fixed-point arithmetic is 23.1 times faster than the conventional method with floating-point arithmetic. Furthermore, they also show the PSNR of LDR images obtained by the proposed method are comparable to those of the conventional method, though reducing computational and memory cost.

Digital map systems can be categorized, based on the support they provide, into map navigation systems and map touring systems. Map navigation systems put more focus on helping travelers finding routes or directions instantly. By contrast, map touring systems such as Google Maps running on desktop computers are built to support users in developing their routes and survey knowledge before they go for travel. In this paper, traveler conceptual models are proposed as an interaction paradigm to enhance user immersion and interaction experience on map touring systems. A map touring system, MapXplorer, is also introduced as a proof of concept with its system design and implementation explained in detail. Twenty participants were invited to join the user study that investigates users' performance and preferences on navigation and exploration tasks. The results of experiments show that the proposed system surpasses traditional map touring systems on both navigation and exploration tasks for about 50 percent on average, and provides better user experience.

Shadow mapping is an efficient method to generate shadows in real time computer graphics and has broad variations from hard to soft shadow synthesis. Soft shadowing based on shadow mapping is a blurring technique on a shadow map or on screen space. Blurring on screen space has an advantage for efficient sampling on a shadow map, since the blurred target array has exactly the same coordinates as the screen. However, a previous blurring method on screen space has a drawback: the generated shadow is not correct when a view direction has a large angle to the normal of the shadowed plane. In this paper, we introduce a new screen space based method for soft shadowing that is fast and generates soft shadows more accurately than the previous screen space soft shadow mapping method. The resultant images show shadows produced by our method just stand in the same place, while shadows by the previous method change in terms of penumbra while the view moves. Surprisingly, although our method is more complex than the previous method, the measurement results of the calculation time show our method is almost the same performance. This is because it controls the blurring area more accurately and thus successfully reduces multiplications for blurring.

In this paper, we propose a superpixel based depth map generation scheme for the application to monoscopic to stereoscopic video conversion. The proposed algorithm employs four main processes to generate depth maps for all frames in the video sequences. First, the depth maps of the key frames in the input sequence are generated by superpixel merging and some user interactions. Second, the frames in the input sequences are over-segmented by Simple Linear Iterative Clustering (SLIC) or depth aided SLIC method depending on whether or not they have the depth maps. Third, each superpixel in current frame is used to match the corresponding superpixel in its previous frame. Finally, depth map is propagated with a joint bilateral filter based on the estimated matching vector of each superpixel. We show an improved performance of the proposed algorithm through experimental results.

A smoothing method for minimum phone error linear regression (MPELR) is proposed in this paper. We show that the objective function for minimum phone error (MPE) can be combined with a prior mean distribution. When the prior mean distribution is based on maximum likelihood (ML) estimates, the proposed method is the same as the previous smoothing technique for MPELR. Instead of ML estimates, maximum a posteriori (MAP) parameter estimate is used to define the mode of prior mean distribution to improve the performance of MPELR. Experiments on a large vocabulary speech recognition task show that the proposed method can obtain 8.4% relative reduction in word error rate when the amount of data is limited, while retaining the same asymptotic performance as conventional MPELR. When compared with discriminative maximum a posteriori linear regression (DMAPLR), the proposed method shows improvement except for the case of limited adaptation data for supervised adaptation.