With the rapid growth of electronic commerce and associated demands on variants of Internet based applications, application systems providing network resources and business services are in high demand around the world. To guarantee robust security and computational efficiency for service retrieval, a variety of authentication schemes have been proposed. However, most of these schemes have been found to be lacking when subject to a formal security analysis. Recently, Chang et al. (2014) introduced a formally provable secure authentication protocol with the property of user-untraceability. Unfortunately, based on our analysis, the proposed scheme fails to provide the property of user-untraceability as claimed, and is insecure against user impersonation attack, server counterfeit attack, and man-in-the-middle attack. In this paper, we demonstrate the details of these malicious attacks. A security enhanced authentication scheme is proposed to eliminate all identified weaknesses.

Emotion recognition via facial expressions (ERFE) has attracted a great deal of interest with recent advances in artificial intelligence and pattern recognition. Most studies are based on 2D images, and their performance is usually computationally expensive. In this paper, we propose a real-time emotion recognition approach based on both 2D and 3D facial expression features captured by Kinect sensors. To capture the deformation of the 3D mesh during facial expression, we combine the features of animation units (AUs) and feature point positions (FPPs) tracked by Kinect. A fusion algorithm based on improved emotional profiles (IEPs) and maximum confidence is proposed to recognize emotions with these real-time facial expression features. Experiments on both an emotion dataset and a real-time video show the superior performance of our method.

We tackle the problem of a biped running over varied and unknown terrain. Running is a necessary skill for a biped moving fast, but it increases the challenge of dynamic balance, especially when a biped is running on varied terrain without terrain information (due to the difficulty and cost of obtaining the terrain information in a timely manner). To address this issue, a new dynamic indicator called the sustainable running criterion is developed. The main idea is to sustain a running motion without falling by maintaining the system states within a running-feasible set, instead of running on a periodic limit cycle gait in the traditional way. To meet the precondition of the criterion, the angular moment about the center of gravity (COG) is restrained close to zero at the end of the stance phase. Then to ensure a small state jump at touchdown on the unknown terrain, the velocity of the swing foot is restrained within a specific range at the end of the flight phase. Finally, the position and velocity of the COG are driven into the running-feasible set. A five-link biped with underactuated point foot is considered in simulations. It is able to run over upward and downward terrain with a height difference of 0.15~m, which shows the effectiveness of our control scheme.

Protein complexes are the basic units of macro-molecular organizations and help us to understand the cell’s mechanism. The development of the yeast two-hybrid, tandem affinity purification, and mass spectrometry high-throughput proteomic techniques supplies a large amount of protein-protein interaction data, which make it possible to predict overlapping complexes through computational methods. Research shows that overlapping complexes can contribute to identifying essential proteins, which are necessary for the organism to survive and reproduce, and for life’s activities. Scholars pay more attention to the evaluation of protein complexes. However, few of them focus on predicted overlaps. In this paper, an evaluation criterion called overlap maximum matching ratio (OMMR) is proposed to analyze the similarity between the identified overlaps and the benchmark overlap modules. Comparison of essential proteins and gene ontology (GO) analysis are also used to assess the quality of overlaps. We perform a comprehensive comparison of serveral overlapping complexes prediction approaches, using three yeast protein-protein interaction (PPI) networks. We focus on the analysis of overlaps identified by these algorithms. Experimental results indicate the important of overlaps and reveal the relationship between overlaps and identification of essential proteins.

Quadrature demodulation is used in medical ultrasound imaging to derive the envelope and instantaneous phase of the received radio-frequency (RF) signal. In quadrature demodulation, RF signal is multiplied with the sine and cosine wave reference signal and then low-pass filtered to produce the base-band complex signal, which has high computational complexity. In this paper, we propose an efficient quadrature demodulation method for B-mode and color flow imaging, in which the RF signal is demodulated by a pair of finite impulse response filters without mixing with the reference signal, to reduce the computational complexity. The proposed method was evaluated with simulation and in vivo experiments. From the simulation results, the proposed quadrature demodulation method produced similar normalized residual sum of squares (NRSS) and velocity profile compared with the conventional quadrature demodulation method. In the in vivo color flow imaging experiments, the time of the demodulation process was 5.66 ms and 3.36 ms, for the conventional method and the proposed method, respectively. These results indicated that the proposed method can maintain the performance of quadrature demodulation while reducing computational complexity.

In some networks nodes belong to predefined groups (e.g., authors belong to institutions). Common network centrality measures do not take this structure into account. Gefura measures are designed as indicators of a node’s brokerage role between such groups. They are defined as variants of betweenness centrality and consider to what extent a node belongs to shortest paths between nodes from different groups. In this article we make the following new contributions to their study: (1) We systematically study unnormalized gefura measures and show that, next to the ‘structural’ normalization that has hitherto been applied, a ‘basic’ normalization procedure is possible. While the former normalizes at the level of groups, the latter normalizes at the level of nodes. (2) Treating undirected networks as equivalent to symmetric directed networks, we expand the definition of gefura measures to the directed case. (3) It is shown how Brandes’ algorithm for betweenness centrality can be adjusted to cover these cases.

This paper presents a multiple target implementation technique for a doubly fed induction generator (DFIG) under unbalanced and distorted grid voltage based on direct power control (DPC). Based on the mathematical model of DFIG under unbalanced and distorted voltage, the proportional and integral (PI) regulator is adopted to regulate the DFIG average active and reactive powers, while the vector PI (VPI) resonant regulator is used to achieve three alternative control targets: (1) balanced and sinusoidal stator current; (2) smooth instantaneous stator active and reactive powers; (3) smooth electromagnetic torque and instantaneous stator reactive power. The major advantage of the proposed control strategy over the conventional method is that neither negative and harmonic sequence decomposition of grid voltage nor complicated control reference calculation is required. The insensitivity of the proposed control strategy to DFIG parameter deviation is analyzed. Finally, the DFIG experimental system is developed to validate the availability of the proposed DPC strategy under unbalanced and distorted grid voltage.