This paper describes latest RF Automated Test Equipment (RF ATE) technologies that include device under test (DUT) connections, a calibration method, and an RF test module mainly focusing on low cost of test (COT). Most important respect for low COT is how achieve a number of simultaneous measurements and short test time as well as a plain calibration. We realized these respects by a newly proposed calibration method and a drastically downsized RF test module with multiple resources and high throughput. The calibration method is very convenient for RF ATE. Major contribution for downsizing of the RF test module is RF circuit technology in form of RF functional system in package (RF-SIPs), resulting in very attractive test solutions.

In OFDMA-based digital duplexing (DD) systems, the effective channel impulse response (CIR) is lengthened due to time difference of arrivals (TDoAs) from adjacent subscriber stations (SSs). In this letter, a time-domain shortening filter (TSF) is proposed to shorten the effective CIR by maximizing signal-to-interference ratio for pulse shortening (SIRPS). A time-domain window (TW) is also proposed to reduce the effect of inter-carrier interference (ICI) due to CFO in OFDMA-based DD systems, by maximizing the signal-to-interference and noise ratio for window (SINRW).

We propose and demonstrate a simple and novel technique to accelerate the carrier injection/depletion processes in an RSOA by applying instantaneous injection/depletion currents at the transition edges of the modulation signal to force the carrier density to respond at a high speed and, as a result, to increase its modulation speed. We theoretically and experimentally show that, by using the proposed technique, it is possible to obtain 5 Gbit/s optical BPSK signal from an RSOA having a modulation bandwidth of only 0.9 GHz.

In this paper, a fast and automated method of counting pedestrians in crowded areas is proposed along with three contributions. We firstly propose Local Empirical Templates (LET), which are able to outline the foregrounds, typically made by single pedestrians in a scene. LET are extracted by clustering foregrounds of single pedestrians with similar features in silhouettes. This process is done automatically for unknown scenes. Secondly, comparing the size of group foreground made by a group of pedestrians to that of appropriate LET captured in the same image patch with the group foreground produces the density ratio. Because of the local scale normalization between sizes, the density ratio appears to have a bound closely related to the number of pedestrians who induce the group foreground. Finally, to extract the bounds of density ratios for groups of different number of pedestrians, we propose a 3D human models based simulation in which camera viewpoints and pedestrians' proximity are easily manipulated. We collect hundreds of typical occluded-people patterns with distinct degrees of human proximity and under a variety of camera viewpoints. Distributions of density ratios with respect to the number of pedestrians are built based on the computed density ratios of these patterns for extracting density ratio bounds. The simulation is performed in the offline learning phase to extract the bounds from the distributions, which are used to count pedestrians in online settings. We reveal that the bounds seem to be invariant to camera viewpoints and humans' proximity. The performance of our proposed method is evaluated with our collected videos and PETS 2009's datasets. For our collected videos with the resolution of 320 × 240, our method runs in real-time with good accuracy and frame rate of around 30 fps, and consumes a small amount of computing resources. For PETS 2009's datasets, our proposed method achieves competitive results with other methods tested on the same datasets [1],[2].

In this paper, we propose a switchable linear prediction (LP)/warped linear prediction (WLP) hybrid scheme for the transform coded excitation (TCX) coder, which is adopted as a core codec in AMR-WB+ and USAC. The proposed algorithm selects either an LP or WLP filter on a per-frame basis. To provide a smooth transitions between LP and WLP frames, a window switching scheme is developed using sine and rectangular windows. In addition, a Gaussian Mixture Model (GMM)-based classification module is used to determine the prediction mode. Through a subjective listening test it was confirmed that the proposed LP/WLP switching scheme offers improved sound quality.

This paper presents a method to improve field uniformity using two TX antennas in a reverberation chamber with less steps of a stirrer. A mode-stirred reverberation chamber (MSRC) is considered as an alternative to the semi-anechoic chamber for an electromagnetic compatibility test because it provides a large test volume, a statistically uniform field, and a high maximum electric field. To improve field uniformity, we introduce two transmitting antennas for excitation in an MSRC, and predict statistical distribution of the complex reflection coefficients (scattering parameters). To prove the validation of our theory and the reliability of measurement results, three kinds of stirrers with different shape and sizes were fabricated and their efficiencies were measured in an MSRC, and then field uniformities have been investigated for 1–3 GHz frequency within the maximum number of independent samples that stirrers can provide. The measurement results show that the average received power is about 1.5 times as high as when using one transmitting antenna, and field uniformity is improved. Use of two transmitting antennas in an MSRC is regarded as a useful method to improve field uniformity at less stirrer steps, for radiated immunity tests.

Execution performance is critical for large-scale and data-intensive workflows. This paper proposes DISWOP, a novel scheduling algorithm for data-intensive workflow optimizations; it consists of three main steps: workflow process generation, task & resource mapping, and task clustering. To evaluate the effectiveness and efficiency of DISWOP, a comparison evaluation of different workflows is conducted a prototype workflow platform. The results show that DISWOP can speed up execution performance by about 1.6-2.3 times depending on the task scale.

This paper presents a novel algorithm to generate homogeneous superpixels from Markov random walks. We exploit Markov clustering (MCL) as the methodology, a generic graph clustering method based on stochastic flow circulation. In particular, we introduce a graph pruning strategy called compact pruning in order to capture intrinsic local image structure. The resulting superpixels are homogeneous, i.e. uniform in size and compact in shape. The original MCL algorithm does not scale well to a graph of an image due to the square computation of the Markov matrix which is necessary for circulating the flow. The proposed pruning scheme has the advantages of faster computation, smaller memory footprint, and straightforward parallel implementation. Through comparisons with other recent techniques, we show that the proposed algorithm achieves state-of-the-art performance.

Ternary content addressable memory (TCAM) is becoming very popular for designing high-throughput forwarding engines on routers. However, TCAM has potential problems in terms of hardware and power costs, which limits its ability to deploy large amounts of capacity in IP routers. In this paper, we propose new hardware architecture for fast forwarding engines, called fast prefix search RAM-based hardware (FPS-RAM). We designed FPS-RAM hardware with the intent of maintaining the same search performance and physical user interface as TCAM because our objective is to replace the TCAM in the market. Our RAM-based hardware architecture is completely different from that of TCAM and has dramatically reduced the costs and power consumption to 62% and 52%, respectively. We implemented FPS-RAM on an FPGA to examine its lookup operation.

The mining of frequent subgraphs from labeled graph data has been studied extensively. Furthermore, much attention has recently been paid to frequent pattern mining from graph sequences. A method, called GTRACE, has been proposed to mine frequent patterns from graph sequences under the assumption that changes in graphs are gradual. Although GTRACE mines the frequent patterns efficiently, it still needs substantial computation time to mine the patterns from graph sequences containing large graphs and long sequences. In this paper, we propose a new version of GTRACE that permits efficient mining of frequent patterns based on the principle of a reverse search. The underlying concept of the reverse search is a general scheme for designing efficient algorithms for hard enumeration problems. Our performance study shows that the proposed method is efficient and scalable for mining both long and large graph sequence patterns and is several orders of magnitude faster than the original GTRACE.

We consider secret key agreement for multiple terminals based on radio propagation characteristics in a wireless relaying system where more than two terminals communicate with each other via a relay. In this system, the multiple terminals share a common secret key generated from their radio propagation characteristics with the help of the relay in the presence of an eavesdropper. In this paper, we present three secret key agreement schemes: an amplify-and-forward (AF) scheme, a signal-combining amplify-and-forward (SC-AF) scheme, and a multiple-access amplify-and-forward (MA-AF) scheme. The key idea of these schemes is that each terminal shares the fading coefficients between all terminals and the relay, and use them as the source of a secret key. The AF scheme is based on a conventional amplify-and-forward two-way relaying method, whereas in the SC-AF scheme and the MA-AF scheme, we apply the idea of analog network coding to secret key agreement. We analyze eavesdropping strategies and show that the AF scheme is not secure if the eavesdropper is located near the relay and can receive signals from the relay without multipath fading and noise. Simulation results show that the SC-AF and MA-AF schemes are effective.

We propose a new coding scheme for lossless bit rate reduction of the MPEG Surround module in unified speech and audio coding (USAC). The proposed scheme is based on context-adaptive arithmetic coding for efficient bit stream composition of spatial parameters. Experiments show that it achieves the significant lossless bit reduction of 9.93% to 12.14% for spatial parameters and 8.64% to 8.96% for the overall MPEG Surround bit streams compared to the original scheme. The proposed scheme, which is not currently included in USAC, can be used for the improved coding efficiency of MPEG Surround in USAC, where the saved bits can be utilized by the other modules in USAC.

Automatic thresholding is an important technique for rail defect detection, but traditional methods are not competent enough to fit the characteristics of this application. This paper proposes the Maximum Weighted Object Correlation (MWOC) thresholding method, fitting the features that rail images are unimodal and defect proportion is small. MWOC selects a threshold by optimizing the product of object correlation and the weight term that expresses the proportion of thresholded defects. Our experimental results demonstrate that MWOC achieves misclassification error of 0.85%, and outperforms the other well-established thresholding methods, including Otsu, maximum correlation thresholding, maximum entropy thresholding and valley-emphasis method, for the application of rail defect detection.

In this paper, we present an automatic vision-based traffic sign recognition system, which can detect and classify traffic signs at long distance under different lighting conditions. To realize this purpose, the traffic sign recognition is developed in an originally proposed dual-focal active camera system. In this system, a telephoto camera is equipped as an assistant of a wide angle camera. The telephoto camera can capture a high accuracy image for an object of interest in the view field of the wide angle camera. The image from the telephoto camera provides enough information for recognition when the accuracy of traffic sign is low from the wide angle camera. In the proposed system, the traffic sign detection and classification are processed separately for different images from the wide angle camera and telephoto camera. Besides, in order to detect traffic sign from complex background in different lighting conditions, we propose a type of color transformation which is invariant to light changing. This color transformation is conducted to highlight the pattern of traffic signs by reducing the complexity of background. Based on the color transformation, a multi-resolution detector with cascade mode is trained and used to locate traffic signs at low resolution in the image from the wide angle camera. After detection, the system actively captures a high accuracy image of each detected traffic sign by controlling the direction and exposure time of the telephoto camera based on the information from the wide angle camera. Moreover, in classification, a hierarchical classifier is constructed and used to recognize the detected traffic signs in the high accuracy image from the telephoto camera. Finally, based on the proposed system, a set of experiments in the domain of traffic sign recognition is presented. The experimental results demonstrate that the proposed system can effectively recognize traffic signs at low resolution in different lighting conditions.

Existing pose estimation algorithms suffer from either low performance or heavy computation cost. In this letter, we present an approach to improve the attractive algorithm called Orthogonal Iteration. A new form of fundamental equations is derived which reduces the computation cost significantly. And paraperspective camera model is used instead of weak perspective camera model during initialization which improves the stability. Experiment results validate the accuracy and stability of the proposed algorithm and show that its computational complexity is favorably compare to the O(n) non-iterative algorithm.

A differential pair of convergent and divergent lenses with adjustable lens spacing (“differential lens”) was devised as a varifocal lens and was successfully integrated into an object-space telecentric lens to build a focus mechanism with constant magnification. This integration was done by placing the front principal point of the varifocal lens at the rear focal point of the telecentric lens within a practical tolerance of positioning. Although the constant-magnification focus mechanism is a parallel projection system, a system for perfect perspective projection imaging without shifting the projection center during focusing could be built simply by properly setting this focus mechanism between an image-taking lens with image-space telecentricity and an image sensor. The focus resolution experimentally obtained was 0.92 µm (σ) for the parallel projection system with a depth range of 1.0 mm and this was 0.25 mm (σ) for the perspective projection system with a range from 120 to 350 mm within a desktop space. A marginal image resolution of 100 lp/mm was obtained with optical distortion of less than 0.2% in the parallel projection system. The differential lens could work up to 55 Hz for a sinusoidal change in lens spacing with a peak-to-valley amplitude of 425 µm when a tiny divergent lens that was plano-concave was translated by a piezoelectric positioner. Therefore, images that were entirely in focus were generated at a frame rate of 30 Hz for an object moving at a speed of around 150 mm/s in depth within the desk top space. Thus, three-dimensional (3-D) imaging that provided 3-D resolution based on fast focusing was accomplished in both microscopic and macroscopic spaces.

This paper proposes a method for reconstructing a smooth and accurate 3D surface. Recent machine vision techniques can reconstruct accurate 3D points and normals of an object. The reconstructed point cloud is used for generating its 3D surface by surface reconstruction. The more accurate the point cloud, the more correct the surface becomes. For improving the surface, how to integrate the advantages of existing techniques for point reconstruction is proposed. Specifically, robust and dense reconstruction with Shape-from-Silhouettes (SfS) and accurate stereo reconstruction are integrated. Unlike gradual shape shrinking by space carving, our method obtains 3D points by SfS and stereo independently and accepts the correct points reconstructed. Experimental results show the improvement by our method.

This paper presents an ADPLL using a hierarchical TDC composed of a 4fLO DCO followed by a divide-by-4 circuit and three stages of known phase interpolators. We derived simple design requirements for ensuring precision of the phase interpolator. The proposed architecture provides immunity to PVT and local variations, which allows calibration-free operation, as well as sub-inverter delay resolution contributing to good in-band phase noise performance. Also the hierarchical TDC makes it possible to employ a selective activation scheme for power saving. Measured performances demonstrate the above advantages and the in-band phase noise reaches -104 dBc/Hz. It is fabricated in a 65 nm CMOS process and the active area is 0.18 mm2.

We propose a fast and precise transient response and frequency characteristics simulation method for switching converters. This method uses a behavioral simulation tool without using a SPICE-like analog simulator. The nonlinear operation of the circuit is considered, and the nonlinear function is realized by defining the nonlinear formula based on the circuit operation and by applying feedback. To assess the accuracy and simulation time of the proposed simulation method, we designed current-mode buck and boost converters and fabricated them using a 0.18-µm high-voltage CMOS process. The comparison in the transient response and frequency characteristics among SPICE, the proposed program on a behavioral simulation tool which we named NSTVR (New Simulation Tool for Voltage Regulators) and experiments of fabricated IC chips showed good agreement, while NSTVR was more than 22 times faster in transient response and 85 times faster in frequency characteristics than SPICE in CPU time in a boost converter simulation.

Lazy-task creation is an efficient method of overcoming the overhead of the grain-size problem in parallel computing. Work stealing is an effective load balancing strategy for parallel computing. In this paper, we present dynamic work stealing strategies in a lazy-task creation technique for efficient fine-grain task scheduling. The basic idea is to control load balancing granularity depending on the number of task parents in a stack. The dynamic-length strategy of work stealing uses run-time information, which is information on the load of the victim, to determine the number of tasks that a thief is allowed to steal. We compare it with the bottommost first work stealing strategy used in StackThread/MP, and the fixed-length strategy of work stealing, where a thief requests to steal a fixed number of tasks, as well as other multithreaded frameworks such as Cilk and OpenMP task implementations. The experiments show that the dynamic-length strategy of work stealing performs well in irregular workloads such as in UTS benchmarks, as well as in regular workloads such as Fibonacci, Strassen's matrix multiplication, FFT, and Sparse-LU factorization. The dynamic-length strategy works better than the fixed-length strategy because it is more flexible than the latter; this strategy can avoid load imbalance due to overstealing.