This letter proposes a noise spectrum estimation algorithm for speech enhancement. The algorithm incorporates the speech presence probability, which is calculated from SNR (signal-to-noise ratio) discrepancy. The discrepancy is measured based on the estimation of the a priori and a posteriori SNR. The proposed algorithm is found to be effective in rapidly switched noise environments. This is confirmed by the experimental results which indicate that the proposed algorithm when integrated in a speech enhancement scheme performs better than conventional noise estimation algorithms.

Even with the recent development of new types of social networking services such as microblogs, Bulletin Board Systems (BBS) remains popular for local communities and vertical discussions. These BBS sites have high volume of traffic everyday with user discussions on a variety of topics. Therefore it is difficult for BBS visitors to find the posts that they are interested in from the large amount of discussion threads. We attempt to explore several main characteristics of BBS, including organizational flexibility of BBS texts, high data volume and aging characteristic of BBS topics. Based on these characteristics, we propose a novel method of Online Topic Detection (OTD) on BBS, which mainly includes a representative post selection procedure based on Markov chain model and an efficient topic clustering algorithm with candidate topic set generation based on Aging Theory. Experimental results show that our method improves the performance of OTD in BBS environment in both detection accuracy and time efficiency. In addition, analysis on the aging characteristic of discussion topics shows that the generation and aging of topics on BBS is very fast, so it is wise to introduce candidate topic set generation strategy based on Aging Theory into the topic clustering algorithm.

This letter deals with a new cell clustering problem subject to signal-to-interference-plus-noise-ratio (SINR) constraints in uplink network MIMO systems, where multiple base stations (BSs) cooperate for joint processing as forming a cluster. We first prove that the SINRs of users in a certain cluster always increase monotonically as the cluster size increases when the receiver filter that maximizes the SINR is used. Using this result, we propose an efficient clustering algorithm to minimize the maximum number of cooperative BSs in a cluster. Simulation results show that the maximum number of cooperative BSs minimized by the proposed method is close to that minimized by the exhaustive search and the proposed scheme outperforms the conventional one in terms of the outage probability.

We propose a fast and resource-efficient agreement protocol on a request set, which is used to realize Byzantine fault tolerant server replication. Although most existing randomized protocols for Byzantine agreement exploit a modular approach, that is, a combination of agreement on a bit value and a reduction of request set values to the bit values, our protocol directly solves the multi-valued agreement problem for request sets. We introduce a novel coin tossing scheme to select a candidate of an agreed request set randomly. This coin toss allows our protocol to reduce resource consumption and to attain faster response time than the existing representative protocols.

MIL-STD-188-220 standard specifies protocols for narrowband and voice-based tactical communication devices. However, the future tactical communication devices require broadband services for accurate command and control. In this letter, the enhancement for MIL-STD-188-220-based systems is proposed for use over wideband channels. Unlike the operation defined in the standard, transmissions in Bump-Slots uses P-Persistence method and give the higher p to stations experiencing longer delays. The proposed method is extensively evaluated and the performance enhancements are proved.

The evolution of wireless communication systems leads to Dynamic Spectrum Allocation for Cognitive Radio, which requires reliable spectrum sensing techniques. Among the spectrum sensing methods proposed in the literature, those that exploit cyclostationary characteristics of radio signals are particularly suitable for communication environments with low signal-to-noise ratios, or with non-stationary noise. However, such methods have high computational complexity that directly raises the power consumption of devices which often have very stringent low-power requirements. We propose a strategy for cyclostationary spectrum sensing with reduced energy consumption. This strategy is based on the principle that p processors working at slower frequencies consume less power than a single processor for the same execution time. We devise a strict relation between the energy savings and common parallel system metrics. The results of simulations show that our strategy promises very significant savings in actual devices.

In this paper, we proposed reduction operators of timed Petri net for efficient model checking. Timed Petri nets are used widely for modeling and analyzing systems which include time concept. Analysis of the system can be done comprehensively with model checking, but there is a state-space explosion problem. Therefore, previous researchers proposed reduction methods and translation methods to timed automata to perform efficient model checking. However, there is no reduction method which consider observability and there is a trade-off between the amount of description and the size of state space. In this paper, first, we have defined a concept of timed behavioral inheritance. Next, we have proposed reduction operators of timed Petri nets based on timed behavioral inheritance. Then, we have applied our proposed operators to an artificial timed Petri net. Moreover, the results show that the reduction operators which consider observability can reduce the size of state space of the original timed Petri nets within the experiment.

Image binarization refers to convert gray-level images into binary ones, and many binarization algorithms have been developed. The related algorithms can be classified as either high quality computation or high speed performance. This letter presents an algorithm that ensures both benefits at the same time. The proposed algorithm intelligently segments input images into several sub-image, after which the sub-image binarization is performed independently. Experimental results reveal that our algorithm provides the appropriate quality with the medium speed.

A data-driven controller has been proposed for nonlinear systems, and its effectiveness has been also shown. However, according to this control scheme, considerable large computation burden is required in on-line learning to update the database. The on-line limit its implementation in industrial processes. In this paper, a controller design scheme is proposed, which enables us to update the database in an off-line manner.

This paper addresses the discrete abstraction problem for stochastic nonlinear systems with continuous-valued state. The proposed solution is based on a function, called the bisimulation function, which provides a sufficient condition for the existence of a discrete abstraction for a given continuous system. We first introduce the bisimulation function and show how the function solves the problem. Next, a convex optimization based method for constructing a bisimulation function is presented. Finally, the proposed framework is demonstrated by a numerical simulation.

This paper proposes a new optimization problem and several implementation algorithms for energy-efficient clouds where energy efficiency is measured by the number of physical machines that can be removed from operation and turned off. The optimization problem is formulated is such a way that solutions are considered favorable not only when the number of migrations is minimized but also when the resulting layout has more free physical machines which can therefore be turned off to save electricity.

This letter proposes a mobile application framework named erasable photograph tagging (EPT) for photograph annotation and fast retrieval. The smartphone owner's voice is employed as tags and hidden in the host photograph without an extra feature database aided for retrieval. These digitized tags can be erased anytime with no distortion remaining in the recovered photograph.

A D2D (Device-to-Device) communication system needs to cope with inter-cell interference and other types of interferences between cellular network and D2D links. As a result, macro user equipments, particularly those located near a cell edge, will suffer from serious link performance degradation. We propose a novel interference avoidance mechanism assisted by the SRN (Shared Relay Node) in this letter. The SRN not only performs data re-transmission as a typical type-II relay, but has several newly defined features to avoid interference between cellular network and D2D links. The superb performance by the proposed scheme is evaluated through extensive system level simulations.

We investigated the filling-in (FI) of line segments at the Artificial Scotoma (AS) created by Motion Induced Blindness (MIB). The FI sensations for line segments were fairly similar to that of the natural Blind Spots (BS), though the geometrical configurations and luminance conditions on stimuli were substantially limited. The 2.5 degree thick black line segment was filled in after 6.5 degree diameter disk was disappeared by MIB. The thin lines, however, didn't fill in. We also obtained the pro and con evidences for the historical FI theory. The disappearance of the uniformly filled circles followed the general FI theory. On the other hand we found it controversial with the FI accounts that the concentric circles disappeared altogether. In the conventional MIB, the target figure disappears and re-appears in a stochastic and spontaneous manner. We devised the novel inducer for MIB so as to yield the synchronization of dis- and re-appearance of the targets with the motion of the inducers. The two stationary disks disappeared in an alternating manner by MIB effects. The subjects observed the background color after disappearance. The alternating disappearance of the two white disks provided the observers with the sensation of the Apparent Motion (AM) of the single disk which would be perceived as jumping up and down. The significant question was raised; did MIB precede AM? When the AM sensation was the case, the percept was not the disappearance but the motion of the single entity. The sensation of the motion provided the almost equivalent conditions to the motion stimuli over the natural BS. We summarized the issue whether the FI at AS by MIB was intrinsically equivalent to the phenomena on BS. The hierarchy of underlying mechanisms of AM and MIB was yet unknown, however, we rather proposed yet another high level motion perception mechanism.

As a next-generation video compression standard, High Efficiency Video Coding (HEVC) achieves enhanced coding performance relative to prior standards such as H.264/AVC. In the new standard, the improved intra prediction plays an important role in bit rate saving. Meanwhile, it also involves significantly increased complexity, due to the adoption of a highly flexible coding unit structure and a large number of angular prediction modes. In this paper, we present a low-complexity intra prediction algorithm for HEVC. We first propose a fast preprocessing stage based on a simplified cost model. Based on its results, a fast prediction unit selection scheme reduces the number of prediction unit (PU) levels that requires fine processing from 5 to 2. To supply PU size decision with appropriate thresholds, a fast training method is also designed. Still based on the preprocessing results, an efficient mode selection scheme reduces the maximum number of angular modes to evaluate from 35 to 8. This achieves further algorithm acceleration by eliminating the necessity to perform fine Hadamard cost calculation. We also propose a 32×32 PU compensation scheme to alleviate the mismatch of cost functions for large transform units, which effectively improves coding performance for high-resolution sequences. In comparison with HM 7.0, the proposed algorithm achieves over 50% complexity reduction in terms of encoding time, with the corresponding bit rate increase lower than 2.0%. Moreover, the achieved complexity reduction is relatively stable and independent to sequence characteristics.

We investigated subjects' gaze movement when reading E-books and compared it with that when reading traditional paper books. By examining the eye motion associated with the reader encountering new lines and new pages during reading, we found that each new line was completed with one saccade in both E-books and paper books, but E-books and paper books differed in saccade patterns when the reader encountered a new page. In E-books, a regular eye movement such as steady gaze to the next page's start position was repeated. In contrast, in paper books, there is no regularity in eye movement during this transition. It was shown that reading behavior is variable and depends on the individual.

This paper is concerned with exploring an extended approach for the stability analysis and synthesis for Markovian jump nonlinear systems (MJNLSs) via fuzzy control. The Takagi-Sugeno (T-S) fuzzy model is employed to represent the MJNLSs with incomplete transition description. In this paper, not all the elements of the rate transition matrices (RTMs), or probability transition matrices (PTMs) are assumed to be known. By fully considering the properties of the RTMs and PTMs, sufficient criteria of stability and stabilization is obtained in both continuous and discrete-time. Stabilization conditions with a mode-dependent fuzzy controller are derived for Markovian jump fuzzy systems in terms of linear matrix inequalities (LMIs), which can be readily solved by using existing LMI optimization techniques. Finally, illustrative numerical examples are provided to demonstrate the effectiveness of the proposed approach.

Packet loss and energy dissipation are two major challenges of designing large-scale wireless sensor networks. Since sensing data is spatially correlated, compressed sensing (CS) is a promising reconstruction scheme to provide low-cost packet error correction and load balancing. In this letter, assuming a multi-hop network topology, we present a CS-oriented data aggregation scheme with a new measurement matrix which balances energy consumption of the nodes and allows for recovery of lost packets at fusion center without additional transmissions. Comparisons with existing methods show that the proposed scheme offers higher recovery precision and less energy consumption on TinyOS.

The fading channel model is seen as an important approach that can efficiently capture the basic time-varying properties of wireless channels, while physical layer security is a promising approach to providing a strong form of security. This paper focuses on the fundamental performance study of applying physical layer security to achieve secure and reliable information transmission over the fading wire-tap channel. For the practical scenario where the main channel is correlated with the eavesdropper channel but only the real time channel state information (CSI) of the main channel is known at the transmitter, we conduct a comprehensive study on the fundamental performance limits of this system by theoretically modeling its secrecy capacity, transmission outage probability and secrecy outage probability. With the help of these theoretical models, we then explore the inherent performance tradeoffs under fading wire-tap channel and also the potential impact of channel correlation on such tradeoffs.

Energy-aware distributed file systems are increasingly moving toward power-proportional designs. However, current works have not considered the cost of updating data sets that were modified in a low-power mode, where a subset of nodes were powered off. In detail, when the system moves to a high-power mode, it must internally replicate the updated data to the reactivated nodes. Effectively reflecting the updated data is vital in making a distributed file system, such as the Hadoop Distributed File System (HDFS), power proportional. In the current HDFS design, when the system changes power mode, the block replication process is ineffectively restrained by a single NameNode because of access congestion of the metadata information of blocks. This paper presents a novel architecture, a NameNode and DataNode Coupling Hadoop Distributed File System (NDCouplingHDFS), which effectively reflects the updated blocks when the system goes into high-power mode. This is achieved by coupling metadata management and data management at each node to efficiently localize the range of blocks maintained by the metadata. Experiments using actual machines show that NDCouplingHDFS is able to significantly reduce the execution time required to move updated blocks by 46% relative to the normal HDFS. Moreover, NDCouplingHDFS is capable of increasing the throughput of the system supporting MapReduce by applying an index in metadata management.