REMUS-II (REconfigurable MUltimedia System 2) is a coarse-grained dynamically reconfigurable computing system for multimedia and communication baseband processing. This paper proposes a real-time H.264 baseline profile encoder on REMUS-II. First, we propose an overall mapping flow for mapping algorithms onto the platform of REMUS-II system and then illustrate it by implementing the H.264 encoder. Second, parallel and pipelining techniques are considered for fully exploiting the abundant computing resources of REMUS-II, thus increasing total computing throughput and solving high computational complexity of H.264 encoder. Besides, some data-reuse schemes are also used to increase data-reuse ratio and therefore reduce the required data bandwidth. Third, we propose a scheduling scheme to manage run-time reconfiguration of the system. The scheduling is also responsible for synchronizing the data communication between tasks and handling conflict between hardware resources. Experimental results prove that the REMUS-MB (REMUS-II version for mobile applications) system can perform a real-time H.264/AVC baseline profile encoder. The encoder can encode CIF@30 fps video sequences with two reference frames and maximum search range of [-16,15]. The implementation, thereby, can be applied to handheld devices targeted at mobile multimedia applications. The platform of REMUS-MB system is designed and synthesized by using TSMC 65 nm low power technology. The die size of REMUS-MB is 13.97 mm2. REMUS-MB consumes, on average, about 100 mW while working at 166 MHz. To my knowledge, in the literature this is the first implementation of H.264 encoding algorithm on a coarse-grained dynamically reconfigurable computing system.

In this letter, three constructions of perfect Gaussian integer sequences are constructed based on cyclic difference sets. Sufficient conditions for constructing perfect Gaussian integer sequences are given. Compared with the constructions given by Chen et al. [12], the proposed constructions relax the restrictions on the parameters of the cyclic difference sets, and new perfect Gaussian integer sequences will be obtained.

In this paper, we present a novel regression-based robust locality preserving projections (RRLPP) method to effectively deal with the issue of noise and occlusion in facial expression recognition. Similar to robust principal component analysis (RPCA) and robust regression (RR) approach, the basic idea of the presented RRLPP approach is also to lead in the low-rank term and the sparse term of facial expression image sample matrix to simultaneously overcome the shortcoming of the locality preserving projections (LPP) method and enhance the robustness of facial expression recognition. However, RRLPP is a nonlinear robust subspace method which can effectively describe the local structure of facial expression images. The test results on the Multi-PIE facial expression database indicate that the RRLPP method can effectively eliminate the noise and the occlusion problem of facial expression images, and it also can achieve better or comparative facial expression recognition rate compared to the non-robust and robust subspace methods meantime.

Two new families of balanced almost binary sequences with a single zero element of period L=2q are presented in this letter, where q=4d+1 is an odd prime number. These sequences have optimal autocorrelation value or optimal autocorrelation magnitude. Our constructions are based on cyclotomy and Chinese Remainder Theorem.

Current sources are essential components for analog circuit designs, the mismatch of which causes the significant degradation of the circuit performance. This paper addresses the mismatch model of CMOS current sources, unlike the conventional modeling, focusing on the layout- and λ-dependency of the process variation, where λ is the output conductance parameter. To make it clear what variation parameter influences the mismatch, we implemented a test chip on 90 nm process technology, where we can collect the characteristics variation data for MOSFETs of various layouts. The test chip also includes D/A converters to check the differential non-linearity (DNL) caused by the mismatch of current sources when behaving as a DAC. Identifying the variation and the circuit-level errors in the measured DNLs, we reveal that our model can more accurately account for the current variation compared to the conventional mismatch model.

In this letter, two new families of quaternary sequences with low four-level or five-level autocorrelation are constructed based on generalized cyclotomy over Z2p. These quaternary sequences are balanced and the maximal absolute value of the out-of-phase autocorrelation is 4.

Binary sequence pairs with optimal periodic correlation have important applications in many fields of communication systems. In this letter, four new families of binary sequence pairs are presented based on the generalized cyclotomy over Z5q, where q ≠ 5 is an odd prime. All these binary sequence pairs have optimal three-level correlation values {-1, 3}.

As technology moves at an annual area density increase rate of 80-120% and channel density moves beyond 3, micro-fluctuation of media recording performance and the homogeneity of media's recording capability become serious reliability concerns in future high density magnetic recording systems. Two concepts are proposed in this work for the characterization of the micro-recording performance fluctuation at high bit and channel densities: recording performance roughness analysis and dynamic magnetic roughness analysis. The recording performance roughness analysis is based on an in-situ measurement technique of the non-linear transition shift (NLTS). Relationship between the performance roughness and the roughness of dynamic magnetic parameters are studied. Results of experimental investigations indicate that the NLTS based performance roughness analysis can reveal more details on media's recording capability and the capability fluctuation--the macro and micro fluctuation of recording performance. The dynamic magnetic roughness analysis is read/write operation based and can be used to characterize the macro and micro fluctuation of media's dynamic magnetic properties. The parameters used for the analysis include media's dynamic coercivity and the dynamic coercive squareness. Here, "dynamic" refers to the dynamic performance measured at MHz frequency. The authors also noticed in their technology development process that further methodology development and confirmation are necessary for media's dynamic performance analysis. Therefore, the work also extends to the accuracy analysis of the playback amplitude based methods for the analysis of the dynamic coercive squareness and dynamic hysteresis loop. A method which is of smaller testing error is identified and reported in this work.

Beamforming with sparse constraint has shown significant performance improvement. In this letter, a least squares constant modulus blind adaptive beamforming with sparse constraint is proposed. Simulation results indicate that the proposed approach exhibits better performance than the well-known least squares constant modulus algorithm (LSCMA).

The electromagnetic force of evanescent field acting on dielectric slab is studied with the use of Maxwell stress tensor. The results show that dielectrics slab may receive always an attractive force when the incident wave is evanescent field while a pressure or an attractive force when the wave is propagating one. The magnitude of the attractive force by evanescent field is much larger than that of the propagating wave. And here some numerical examples are given.

Maximizing the profit of datacenter networks (DCNs) demands to satisfy more flows' requirements simultaneously, but existing schemes always allocate resource based on single flow attribute, which cannot carry out accurate resource allocation and make many flows failed. In this letter, we propose Highest Priority Flow First (HPFF) to maximize DCN profit, which allocates resource for flows according to the priority. HPFF employs a utility function that considers multiple flow attributes, including flow size, deadline and demanded bandwidth, to calculate the priority for each flow. The experiments on the testbed show that HPFF can improve the network profit by 6.75%-19.7% and decrease the number of failed flow by 26.3%-83.3% compared with existing schemes under real DCN workloads.

Hybrid wired/wireless on-chip network is a promising communication architecture for multi-/many-core SoC. For application-specific SoC design, it is important to design a dedicated on-chip network architecture according to the application-specific nature. In this paper, we propose a heuristic wireless link allocation algorithm for creating hybrid on-chip network architecture. The algorithm can eliminate the performance bottleneck by replacing multi-hop wired paths by high-bandwidth single-hop long-range wireless links. The simulation results show that the hybrid on-chip network designed by our algorithm improves the performance in terms of both communication delay and energy consumption significantly.

TCP Friendly Rate Control (TFRC) has been widely used in the Internet multimedia streaming applications. However, performance of traditional TFRC algorithm degrades significantly when deployed over wireless networks. Although numerous TFRC variants have been proposed to improve the performance of TFRC over wireless networks, designing a TFRC algorithm with graceful performance both in throughput and fairness still remains a great challenge. In this paper, a novel TFRC algorithm, named TFRC-FIT, is proposed to improve the performance of TFRC over wireless environments. In the proposed approach, the behavior of multiple TFRC flows is simulated in single connection, while the number of simulated flows is adjusted by the network queuing delay. Through this mechanism, TFRC-FIT can fully utilize the capacity of wireless networks, while maintaining good fairness and TCP friendliness. Both theoretical analysis and extensive experiments over hardware network emulator, Planetlab test bed as well as commercial 3G wireless networks are carried out to characterize and validate the performance of our proposed approach.

In this letter, constructions of sequences with perfect odd autocorrelation and sequence sets with zero odd correlation zone (ZOCZ) over the 8-QAM+ constellation are presented. Based on odd perfect ternary sequences, odd perfect sequences and ZOCZ sequence sets over the 8-QAM+ constellation are constructed by using shift vectors and mappings. These odd perfect sequences and ZOCZ sequence sets over 8-QAM+ constellation can be used in communication systems to achieve high transmission data rate (TDR) and low interference.

In integrated circuit design of advanced technology nodes, layout density uniformity significantly influences the manufacturability due to the CMP variability. In analog design, especially, designers are suffering from passing the density checking since there are few useful tools. To tackle this issue, we focus a transistor-array(TA)-style analog layout, and propose a density optimization algorithm consistent with complicated design rules. Based on TA-style, we introduce a density-aware layout format to explicitly control the layout pattern density, and provide the mathematical optimization approach. Hence, a design flow incorporating our density optimization can drastically reduce the design time with fewer iterations. In a design case of an OPAMP layout in a 65nm CMOS process, the result demonstrates that the proposed approach achieves more than 48× speed-up compared with conventional manual layout, meanwhile it shows a good circuit performance in the post-layout simulation.

A method which uses the moving time and the over travel time of contact to discover the characteristics of contact and the reliability of aerospace relay is proposed. The Gauss-Newton method and its improved form (Macalto method) are used to identify the nonlinear mathematical model of the parameter during armature initial moving period, which is from the coil is energized at a rated voltage to the moment the armature begins to move. The validity of the method is verified by results of actual experiments and analysis.

This letter proposes a fast superpixel segmentation method based on boundary sampling and interpolation. The basic idea is as follow: instead of labeling local region pixels, we estimate superpixel boundary by interpolating candidate boundary pixel from a down-sampling image segmentation. On the one hand, there exists high spatial redundancy within each local region, which could be discarded. On the other hand, we estimate the labels of candidate boundary pixels via sampling superpixel boundary within corresponding neighbour. Benefiting from the reduction of candidate pixel distance calculation, the proposed method significantly accelerates superpixel segmentation. Experiments on BSD500 benchmark demonstrate that our method needs half the time compared with the state-of-the-arts while almost no accuracy reduction.

With the rapid growth of wireless networks and great success of Internet video, wireless video services are expected to be widely deployed in the near future. As different types of wireless networks are converging into all IP networks, i.e., the Internet, it is important to study video delivery over the wireless Internet. This paper proposes a novel end-system based adaptation protocol called Wireless Hybrid Adaptation Layered Multicast (WHALM) protocol for layered video multicast over wireless Internet. In WHALM the sender dynamically collects bandwidth distribution from the receivers and uses an optimal layer rate allocation mechanism to reduce the mismatches between the coarse-grained layer subscription levels and the heterogeneous and dynamic rate requirements from the receivers, thus maximizing the degree of satisfaction of all the receivers in a multicast session. Based on sampling theory and theory of probability, we reduce the required number of bandwidth feedbacks to a reasonable degree and use a scalable feedback mechanism to control the feedback process practically. WHALM is also tuned to perform well in wireless networks by integrating an end-to-end loss differentiation algorithm (LDA) to differentiate error losses from congestion losses at the receiver side. With a series of simulation experiments over NS platform, WHALM has been proved to be able to greatly improve the degree of satisfaction of all the receivers while avoiding congestion collapse on the wireless Internet.

Macroscopic method for quantization of the evanescent fields brought about by total reflection is presented. Here, a semi-infinite space is assumed to be filled with a transparent dispersive dielectric with dielectric constant ε(ω) to the left of the plane z = 0, and be empty to the right of the plane. The wave is assumed to be incident from the left, and so the whole field is composed of the triplet of incident, reflected, and transmitted waves labeled by a continuous wave vector index. The transmitted wave in free space may be evanescent. The triplet is shown exactly without using slowly varying field approximation in dispersive medium to form orthogonal mode for different wave vectors, which provides the basis for the quantization of the triplet with taken into account of medium dispersion. The exact orthogonal relation reduces to the well known one if the dielectric is nondispersive, ε/ω = 0. By using the field expansion in terms of the orthogonal triplet modes, the total field energy is found to be the sum of the energies of independent harmonic oscillators. A discussion is also made on the wave momentum of evanescent field.

Cloud computing, a novel distributed paradigm to provide powerful computing capabilities, is usually adopted by developers and researchers to execute complicated IoT applications such as complex workflows. In this scenario, it is fundamentally important to make an effective and efficient workflow application scheduling and execution by fully utilizing the advantages of the cloud (as virtualization and elastic services). However, in the current stage, there is relatively few research for workflow scheduling in cloud environment, where they usually just bring the traditional methods directly into cloud. Without considering the features of cloud, it may raise two kinds of problems: (1) The traditional methods mainly focus on static resource provision, which will cause the waste of resources; (2) They usually ignore the performance fluctuation of virtual machines on the physical machines, therefore it will lead to the estimation error of task execution time. To address these problems, a novel mechanism which can estimate the probability distribution of subtask execution time based on background VM load series over physical machines is proposed. An elastic performance fluctuations-aware stochastic scheduling algorithm is introduced in this paper. The experiments show that our proposed algorithm can outperform the existing algorithms in several metrics and can relieve the influence of performance fluctuations brought by the dynamic nature of cloud.