A procedural terrain generation method is presented in this paper. It uses a user-drawn sketch map, which is a raster image with lines and polygons painted by different colors to represent sketches of different terrain features, as input to control the placement of terrain features. Some simple parameters which can be easily understood and adjusted by users are used to control the generation process. To further automatically generate terrains, a mechanism that automatically generates sketches is also put forward. The method is implemented in a PC, and experiments show that terrains are generated efficiently. This method provides users a controllable way to generate terrains.

Reprogramming for wireless sensor networks is essential to upload new code or to alter the functionality of existing code. To overcome the weakness of the centralized approach of the traditional solutions, He et al. proposed the notion of distributed reprogramming where multiple authorized network users are able to reprogram sensor nodes without involving the base station. They also gave a novel distributed reprogramming protocol called SDRP by using identity-based signature, and provided a comprehensive security analysis for their protocol. In this letter, unfortunately, we demonstrate that SDRP is insecure as the protocol fails to satisfy the property of authenticity and integrity of code images, the most important security requirement of a secure reprogramming protocol.

Many successful methods for recognizing human action are spatio-temporal interest point (STIP) based methods. Given a test video sequence, for a matching-based method using a voting mechanism, each test STIP casts a vote for each action class based on its mutual information with respect to the respective class, which is measured in terms of class likelihood probability. Therefore, two issues should be addressed to improve the accuracy of action recognition. First, effective STIPs in the training set must be selected as references for accurately estimating probability. Second, discriminative STIPs in the test set must be selected for voting. This work uses ε-nearest neighbors as effective STIPs for estimating the class probability and uses a variance filter for selecting discriminative STIPs. Experimental results verify that the proposed method is more accurate than existing action recognition methods.

Content addressable memory is widely used for fast lookup table data searching, but it often consumes considerable power. Moreover, designing the suitable content addressable memory architecture for a specific application also consumes lots of time, since the behavioral simulation is often done in the transistor level. SystemC is a system-level modeling language and simulation platform, providing high simulation efficiency for hardware software co-design. Unfortunately, SystemC does not provide the function for estimating power dissipation of a structure design. In this paper, a SystemC-based fast content addressable memory power estimation method is presented for estimating the power dissipation of the match-line circuit, the search-line circuit, and the storage cell array of content addressable memory in the early design stage. The mathematical equations and behavioral patterns are used as the inputs of power estimation model. The simulation results based on 10 Mibench benchmarks show that the simulation time of the proposed method is in average 1233 times faster than that of HSPICE simulator with only 3.51% error rate.

Maximum margin clustering (MMC) is a newly proposed clustering method that extends the large-margin computation of support vector machine (SVM) to unsupervised learning. Traditionally, MMC is formulated as a nonconvex integer programming problem which makes it difficult to solve. Several methods rely on reformulating and relaxing the nonconvex optimization problem as semidefinite programming (SDP) or second-order cone program (SOCP), which are computationally expensive and have difficulty handling large-scale data sets. In linear cases, by making use of the constrained concave-convex procedure (CCCP) and cutting plane algorithm, several MMC methods take linear time to converge to a local optimum, but in nonlinear cases, time complexity is still high. Since extreme learning machine (ELM) has achieved similar generalization performance at much faster learning speed than traditional SVM and LS-SVM, we propose an extreme maximum margin clustering (EMMC) algorithm based on ELM. It can perform well in nonlinear cases. Moreover, the kernel parameters of EMMC need not be tuned by means of random feature mappings. Experimental results on several real-world data sets show that EMMC performs better than traditional MMC methods, especially in handling large-scale data sets.

This paper concerns a problem of on-line model parameter estimations for multiple time-delay systems. In order to estimate unknown model parameters from measured state variables, we propose two schemes using Lyapunov's direct method, called parallel and series-parallel model estimators. It is shown through a numerical example that the proposed parallel and series-parallel model estimators can be effective when sufficiently rich inputs are applied.

As mobile multimedia services expand, user behavior will become more diverse and the control of service quality from the user's perspective will become more important in service design. The quality of the network is one of the critical factors determining mobile service quality. However, this has mainly been evaluated in objective physical terms, such as delay reduction and bandwidth expansion. It is less common to use a human-centered design viewpoint when improving network performance. In this paper, we discuss ways to improve the quality of web services using time-fillers that actively address the human factors to improve the subjective quality of a mobile network. A field experiment was conducted, using a prototype. The results of the field experiment show that time-fillers can significantly decrease user dissatisfaction with waiting, but that this effect is strongly influenced by user preferences concerning content. Based on these results, we discuss the design requirements for effective use of time-fillers.

One of the largest challenges for coarse-grained reconfigurable arrays (CGRAs) is how to efficiently map applications. The key issues for mapping are (1) how to reduce the memory bandwidth, (2) how to exploit parallelism in algorithms and (3) how to achieve load balancing and take full advantage of the hardware potential. In this paper, we propose a novel parallelism scheme, called ‘Hybrid partitioning’, for mapping a H.264 high definition (HD) decoder onto REMUS-II, a CGRA system-on-chip (SoC). Combining good features of data partitioning and task partitioning, our methodology mainly consists of three levels from top to bottom: (1) hybrid task pipeline based on slice and macroblock (MB) level; (2) MB row-level data parallelism; (3) sub-MB level parallelism method. Further, on the sub-MB level, we propose a few mapping strategies such as hybrid variable block size motion compensation (Hybrid VBSMC) for MC, 2D-wave for intra 44, parallel processing order for deblocking. With our mapping strategies, we improved the algorithm's performance on REMUS-II. For example, with a luma 1616 MB, the Hybrid VBSMC achieves 4 times greater performance than VBSMC and 2.2 times greater performance than fixed 44 partition approach. Finally, we achieve 1080p@33fps H.264 high-profile (HiP)@level 4.1 decoding when the working frequency of REMUS-II is 200 MHz. Compared with typical hardware platforms, we can achieve better performance, area, and flexibility. For example, our performance achieves approximately 175% improvement than that of a commercial CGRA processor XPP-III while only using 70% of its area.

Many High-Dynamic-Range (HDR) rendering techniques have been developed. Of these, the image color appearance model, iCAM, is a typical HDR image rendering algorithm. HDR rendering methods normally require a tone compression process and include many color space transformations from the RGB signal of an input image to the RGB signal of output devices for the realistic depiction of a captured image. The iCAM06, which is a refined iCAM, also contains a tone compression step and several color space conversions for HDR image reproduction. On the other hand, the tone compression and frequent color space changes in the iCAM06 cause color distortion, such as a hue shift and saturation reduction of the output image. To solve these problems, this paper proposes a separate color correction method that has no effect on the output luminance values by controlling only the saturation and hue of the color attributes. The color saturation of the output image was compensated for using the compensation gain and the hue shift was corrected using the rotation matrix. The separate color correction method reduces the existing color changes in iCAM06. The compensation gain and rotation matrix for the color correction were formulated based on the relationship between the input and output tristimulus values through the tone compression. The experimental results show that the revised iCAM06 with the proposed method has better performance than the default iCAM06.

The purpose of this study is to develop an automated scheme of carotid artery calcification (CAC) detection on dental panoramic radiographs (DPRs). The CAC is one of the indices for predicting the risk of arteriosclerosis. First, regions of interest (ROIs) that include carotid arteries are determined on the basis of inflection points of the mandibular contour. Initial CAC candidates are detected by using a grayscale top-hat filter and a simple grayscale thresholding technique. Finally, a rule-based approach and a support vector machine to reduce the number of false positive (FP) findings are applied using features such as area, location, and circularity. A hundred DPRs were used to evaluate the proposed scheme. The sensitivity for the detection of CACs was 90% with 4.3 FPs (80% with 1.9 FPs) per image. Experiments show that our computer-aided detection scheme may be useful to detect CACs.

Multicode CDMA systems convert a high-rate serial data stream into low-rate parallel data streams prior to transmission, but reducing the peak-to-average-power-ratio (PAPR) is a prerequisite. In this paper, we propose constant amplitude coding schemes with forward error correction (EC) capability. The proposed schemes overcome the adverse nonlinear effects of the high power amplifier (HPA) by using the transmitted signal of constant amplitude and parity channel. In the first scheme, we add the EC capability to the previously reported constant-amplitude rate 4/4 (Suil's) scheme, which can transmit data without energy loss. Next, we propose a rate 12/16 decoder with EC capability, which is slightly different from the previous work through the addition of EC capability. Lastly, we propose a new high-rate EC capable 16/16 scheme without energy loss, which makes it superior to the conventional 12/16 scheme which experiences excessive energy loss due to redundancy. Computer simulation results confirm that new 4/4 decoder along with 12/16 decoder and 16/16 encoder/decoder can effectively reduce the inherent problem of high PAPR in the multicode CDMA signal transmission. Our methods also yield better BER performance than other constant amplitude coding schemes.

Communication among isolated networks (clusters) in delay tolerant networks (DTNs) can be supported by a message ferry, which collects bundles from clusters and delivers them to a sink node. When there are lots of distant static clusters, multiple message ferries and sink nodes will be required. In this paper, we aim to make groups, each of which consists of physically close clusters, a sink node, and a message ferry. Our objective is minimizing the overall mean delivery delay of bundles in consideration of both the offered load of clusters and distances between clusters and their sink nodes. Based on existing work, we first model this problem as a nonlinear integer programming. Using a commercial nonlinear solver, we obtain a quasi-optimal grouping. Through numerical evaluations, we show the fundamental characteristics of grouping, the impact of location limitation of base clusters, and the relationship between delivery delay and the number of base clusters.

A selfish routing game is a simple model of selfish behaviors in networks. It is called that Braess's paradox occurs in the selfish routing game if an equilibrium flow achieved by players' selfish behaviors is not the optimal minimum latency flow. In order to make the minimum latency flow a Nash equilibrium, a marginal cost tax has been proposed. Braess graphs have also been proposed to discuss Braess's paradox. In a large population of selfish players, conflicts between purposes of each player and the population causes social dilemmas. In game theory, to resolve the social dilemmas, a capitation tax and/or a subsidy has been introduced, and players' dynamical behaviors have been formulated by replicator dynamics. In this paper, we formulate replicator dynamics in the Braess graphs and investigate stability of the minimum latency flow with and without the marginal cost tax. An additional latency caused by the marginal cost tax is also shown. To resolve the problem of the additional latency, we extend the capitation tax and the subsidy to a state-dependent tax and apply it to the stabilization problem of the minimum latency flow.

With the technology scaling down, leakage power becomes an important part of total power consumption. The relatively large leakage current weakens the energy recovery capability of adiabatic circuits and reduces its superiority, compared with static CMOS circuits in the field of low-power design. In this paper, we rebuild three types of adiabatic circuits (2N2N2P, IPAL and DCPAL) based on FinFET devices to obtain a large leakage power reduction by rationally utilizing the different operating modes of FinFET devices (SG, LP, and IG). A 16-bit adiabatic adder has been investigated to demonstrate the advantages of FinFET adiabatic circuits. The Predictive Technology Model (PTM) is used for 32-nm bulk MOSFET and FinFET devices and all of the simulations are based on HSPICE. The results evince the proposed FinFET adiabatic circuits have a considerable reduction (more than 60% for SG mode FinFET and more than 80% for LP mode FinFET) of power consumption compared with the bulk MOSFET ones. Furthermore, the FinFET adiabatic circuits also have higher limiting frequency of clock source and better noise immunity.

Clustering methods are divided into hierarchical clustering, partitioning clustering, and more. K-Means is a method of partitioning clustering. We improve the performance of a K-Means, selecting the initial centers of a cluster through a calculation rather than using random selecting. This method maximizes the distance among the initial centers of clusters. Subsequently, the centers are distributed evenly and the results are more accurate than for initial cluster centers selected at random. This is time-consuming, but it can reduce the total clustering time by minimizing allocation and recalculation. Compared with the standard algorithm, F-Measure is more accurate by 5.1%.

Segmenting indicated objects from natural color images remains a challenging problem for researches of image processing. In this paper, a novel level set approach is presented, to address this issue. In this segmentation algorithm, a contour that lies inside a particular region of the concerned object is first initialized by a user. The level set model is then applied, to extract the object of arbitrary shape and size containing this initial region. Constrained on the position of the initial contour, our proposed framework combines two particular energy terms, namely local and global energy, in its energy functional, to control movement of the contour toward object boundaries. These energy terms are mainly based on graph partitioning active contour models and Bhattacharyya flow, respectively. Its flow describes dissimilarities, measuring correlative relationships between the region of interest and surroundings. The experimental results obtained from our image collection show that the suggested method yields accurate and good performance, or better than a number of segmentation algorithms, when applied to various natural images.

Two voltage controlled current source (VCCS) models of double-channel p-type lateral extended drain MOS (DPLEDMOS) are firstly proposed to analyze the energy recovery circuit (ERC) efficiency of PDP data driver IC. In terms of the mathematical function between ID and VDS, the VCCS models are created. The presented models can be embedded in system software Saber to simulate the ERC waveform of data driver IC. A test board and a PDP system are used to verify the accuracy of the VCCS models. The experimental measurements agree with the simulation results very well and the maximum model error is 3.89%. Simulation results also show that the ERC efficiency of PDP data driver IC is influenced by three factors: the value of charge time TERC, the drain current ID, and the capacitance of CL. In an actual PDP system, TERC is restricted and CL is changeless. The ERC efficiency of PDP data driver IC can be improved significantly by using DPLEDMOS which has higher ID capacity. The proposed VCCS models of DPLEDMOS can be used to predict the ERC efficiency accurately.

In this paper, we design a new color space YUskin Vskin from YUV color space, based on the principle of skin color with respect to the change of color temperature. Compared with previous work, this color space proved to be the optimal color space for hand segmentation with linear thresholds. We also propose a novel fingertip detection method based on the concomitance between finger and fingernail. The two techniques together improve the performance of hand contour and fingertip extraction in hand gesture recognition.

This paper proposes the physical architecture of an electric power system with multiple homes. The notion of home is a unit of small-scale power system that includes local energy source, energy storage, load, power conversion circuits, and control systems. An entire power system consists of multiple homes that are interconnected via a distribution network and that are connected to the commercial power grid. The interconnection is autonomously achieved with a recently developed technology of grid-connected inverters. A mathematical model of slow dynamics of the power system is also developed in this paper. The developed model enables the evaluation of steady and transient characteristics of power systems.

The 60GHz millimeter-wave (mmWave) wireless technology is a focus of increasing attention, since its ability to transmit more than Gbps PHY data rate makes it suitable for high-speed, short-range applications such as peer-to-peer synchronization and kiosk terminals. In the case of short-range communication with a range of several tens of centimeters, only terminals present in this communication range will be affect and communication is considered to be on a one-to-one basis. In one-to-one communication, a simpler and more efficient access mechanism is preferable. The ability of current CSMA/CA based MAC, for example MAC of IEEE 802.11 WLAN systems, to achieve high throughput is limited by the low MAC efficiency caused by high signal exchange overhead, such as interframe space (IFS) and acknowledgement. This paper proposes an ACK/NACK mechanism that enhances the throughput in short-range one-to-one communication. The ACK/NACK mechanism uses Negative ACK (NACK) as the acknowledgement policy to reduce the overhead of ACK and the transmitter switches the required acknowledgement policy to ACK based on a switchover threshold. It solves a problem arising from NACK, namely, that NACK has no mechanism for keeping alive. We evaluate the throughput of the ACK/NACK mechanism by both theoretical analysis and computer simulation. The proposed ACK/NACK mechanism is implemented in 65 nm CMOS process (BBIC); we connect this BBIC to a 60 GHz RFIC and exchange frames wirelessly. In this experiment, it is verified that the ACK/NACK mechanism enhances throughput.