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.

An asymmetric classifier based on kernel partial least squares is proposed for software defect prediction. This method improves the prediction performance on imbalanced data sets. The experimental results validate its effectiveness.

We propose an anomaly detection method for finding patterns in network traffic that do not conform to legitimate (i.e., normal) behavior. The proposed method trains a baseline model describing the normal behavior of network traffic without using manually labeled traffic data. The trained baseline model is used as the basis for comparison with the audit network traffic. This anomaly detection works in an unsupervised manner through the use of time-periodic packet sampling, which is used in a manner that differs from its intended purpose – the lossy nature of packet sampling is used to extract normal packets from the unlabeled original traffic data. Evaluation using actual traffic traces showed that the proposed method has false positive and false negative rates in the detection of anomalies regarding TCP SYN packets comparable to those of a conventional method that uses manually labeled traffic data to train the baseline model. Performance variation due to the probabilistic nature of sampled traffic data is mitigated by using ensemble anomaly detection that collectively exploits multiple baseline models in parallel. Alarm sensitivity is adjusted for the intended use by using maximum- and minimum-based anomaly detection that effectively take advantage of the performance variations among the multiple baseline models. Testing using actual traffic traces showed that the proposed anomaly detection method performs as well as one using manually labeled traffic data and better than one using randomly sampled (unlabeled) traffic data.

A flexible and computationally efficient method for spectral analysis of sinusoidal signals using the Basis Pursuit De-Noising (BPDN) is proposed. This method estimates a slotted Auto-Correlation Function (ACF) and computes the spectrum as the sparse representation of the ACF in a dictionary of cosine functions. Simulation results illustrate flexibility and effectiveness of the proposed method.

In this paper, we propose a method capable of shortening the distance from a noise detection microphone to a loudspeaker in active noise control system with non-minimum phase secondary path. The distance can be basically shortened by forming the noise control filter, which produces the secondary noise provided by the loudspeaker, with the cascade connection of a non-recursive filter and a recursive filter. The output of the recursive filter, however, diverges even when the secondary path includes only a minimum phase component. In this paper, we prevent the divergence by utilizing MINT (multi-input/output inverse theorem) method increasing the number of secondary paths than that of primary paths. MINT method, however, requires a large scale inverse matrix operation, which increases the processing cost. We hence propose a method reducing the processing cost. Actually, MINT method has only to be applied to the non-minimum phase components of the secondary paths. We hence extract the non-minimum phase components and then apply MINT method only to those. The order of the inverse matrix thereby decreases and the processing cost can be reduced. We finally show a simulation result demonstrating that the proposed method successfully works.

The conventional semi-orthogonal user pairing algorithm in uplink virtual MIMO systems can be used to improve the total system throughput but it usually fails to maintain good throughput performance for users experiencing relatively poor channel conditions. A novel user paring algorithm is presented in this paper to solve this fairness issue. Based on our analysis of the MMSE receiver, a new criterion called “inverse selection” is proposed for use in conjunction with the semi-orthogonal user selection. Simulation results show that the proposed algorithm can significantly improve the throughput of users with poor channel condition at only a small reduction of the overall throughput.

In order to realize millimeter-wave (MMW) 3-D system-in-package (SiP) front-end modules, we propose a 60-GHz band copper ball vertical interconnection structure, which interconnects between vertically stacked substrates. The structure enables ICs to be placed between the vertically stacked substrates. Since the diameter of the copper balls must exceed the thickness of the ICs, the distance between the substrates in the modules is larger than that of the flip-chip interconnection widely used in the MMW-band. Therefore, the conventional flip-chip interconnection does not scale for the interconnection between the substrates in MMW 3-D SiP front-end modules. The layout of grounded copper balls and the patterns of inner ground layers in the upper/lower substrates are designed using 3-D electromagnetic field simulation. The designed structure allows less than 1 dB transmission loss up to 71.1 GHz, compared with a through transmission line. The result is verified with fabrication and measurement and confirms the feasibility of MMW 3-D SiP front-end modules.

This work presents a real-time human detection system for VGA (Video Graphics Array, 640480) video, which well suits visual surveillance applications. To achieve high running speed and accuracy, firstly we design multiple fast scalar feature types on the gradient channels, and experimentally identify that NOGCF (Normalized Oriented Gradient Channel Feature) has better performance with Gentle AdaBoost in cascaded classifiers. A confidence measure for cascaded classifiers is developed and utilized in the subsequent tracking stage. Secondly, we propose to use speedup techniques including a detector pyramid for multi-scale detection and channel compression for integral channel calculation respectively. Thirdly, by integrating the detector's discrete detected humans and continuous detection confidence map, we employ a two-layer tracking by detection algorithm for further speedup and accuracy improvement. Compared with other methods, experiments show the system is significantly faster with 20 fps running speed in VGA video and has better accuracy as well.

The existing routing protocols for the interplanetary backbone network did not consider future link connection and link congestion. A novel routing protocol named CAMARP for the interplanetary backbone network is proposed in this letter. We use wait delay to consider future link connection and make the best next hop selection. A load balancing mechanism is used to avoid congestion. The proposed method leads to a better and more efficient distribution of traffic, and also leads to lower packet drop rates and higher throughput. CAMARP demonstrates good performance in the experiment.

In DC/DC converters with low output voltage and high output current, the technique of synchronous rectification is widely used for improving the output efficiency. However, SR buck converters can experience the abnormal phenomenon called “self turn-on” which will occur in the low-side switch under some circuit conditions. “Self turn-on” is a malfunction of the low-side switch, basically caused by the resonance of the parasitic inductance and the parasitic capacitance. It results in noticeable power dissipation. In this paper, the phenomenon will be clearly described and investigated. With the theoretical analysis and the experimental verification, strategies that can suppress this phenomenon are proposed.

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.

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.

Multimedia transactions between vehicles are expected to become a promising application in VANETs but security is a fundamental issue that must be resolved before such transactions can become practical and trusted. Existing certificate-based digital signature schemes are ineffective for ensuring the security of multimedia transactions in VANETs. This ineffectiveness exists because there is no guarantee that (1) vehicles can download the latest certificate revocation lists or that (2) vehicles can complete a multimedia transaction before leaving their communication range. These two problems result, respectively, from a lack of infrastructure and from the inconsistent connectivity inherent in VANETs. In this paper, we propose a digital signature approach that combines a certificateless signature scheme and short-lived public keys to alleviate these problems. We then propose a security protocol that uses the proposed signature approach for multimedia transactions between vehicles. The proposed protocol enables vehicles to trade in multimedia resources without an online trust authority. We provide an analytical approach to optimizing the security of the proposed protocol. The security and performance of our protocol are evaluated via simulation and theoretical analysis. Based on these evaluations, we contend that the proposed protocol is practical for multimedia transactions in VANETs in terms of security and performance.

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.

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.

In this paper, to reduce the memory size requirements of IFFT for OFDM-based applications, we propose a new IFFT design technique based on a combined integer mapping of three IFFT input signals: modulated data, pilot and null signals. The proposed method focuses on reducing the size of memory cells in the first two stages of the single-path delay feedback (SDF) IFFT architectures since the first two stages require 75% of the total memory cells. By simulations of 2048-point IFFT design for cognitive radio systems, it is shown that the proposed IFFT design method achieves more than 13% reduction in gate count and 11% reduction in power consumption compared with conventional IFFT design.

This paper proposes a method of accurately detecting the boundary of narrow stripes, such as lane markings, by employing gradient cues of edge points. Using gradient direction cues, the edge points at the two sides of the boundary of stripes are classified into two groups before the Hough transform is applied to extract the boundary lines. The experiments show that the proposed method improves significantly the performance in terms of the accuracy of boundary detection of narrow stripes over the conventional approaches without edge point grouping.

A 315 MHz power-gated ultra low power transceiver for wireless sensor network is developed in 40 nm CMOS. The developed transceiver features an injection-locked frequency multiplier for carrier generation and a power-gated low noise amplifier with current second-reuse technique for receiver front-end. The injection-locked frequency multiplier implements frequency multiplication by edge-combining and thereby achieves 11 µW power consumption at 315 MHz. The proposed low noise amplifier achieves the lowest power consumption of 8.4 µW with 7.9 dB noise figure and 20.5 dB gain in state-of-the-art designs.

In this paper, we propose a new method for the bias-dependent parameter extraction of a MOSFET, which covers DC to over 100 GHz. The DC MOSFET model provided by the chip foundry is assumed to be correct, and the core DC characteristics are designed to be asymptotically recovered at low frequencies. This is carried out by representing the corrections required at high frequencies using a bias-dependent Y matrix, assuming that a parasitic nonlinear two-port matrix (Y-wrapper) is connected in parallel with the core MOSFET. The Y-wrapper can also handle the nonreciprocity of the parasitic components, that is, the asymmetry of the Y matrix. The reliability of the Y-wrapper model is confirmed through the simulation and measurement of a one-stage common-source amplifier operating at several bias points. This paper will not discuss about non-linearity.

The market growths of smart-phones and thin clients have been significantly increasing communication traffic in mobile networks. To handle the increased traffic, network operators should consider how to leverage distributed wireless resources such as distributed spots of wireless local access networks. In this paper, we consider the system where multiple moving users share distributed wireless access points on their traveling routes between their start and goal points and formulate as an optimization problem. Then, we come up with three algorithms as a solution for the problem. The key idea here is 'longcut route instruction', in which users are instructed to choose a traveling route where less congested access points are available; even if the moving distance increases, the throughput for users in the system would improve. In this paper, we define the gain function. Moreover, we analyze the basic characteristics of the system using as a simple model as possible.