Transfer boosting, a branch of instance-based transfer learning, is a commonly adopted transfer learning method. However, currently popular transfer boosting methods focus on binary classification problems even though there are many multi-classification tasks in practice. In this paper, we developed a new algorithm called MultiTransferBoost on the basis of TransferBoost for multi-classification. MultiTransferBoost firstly separated the multi-classification problem into several orthogonal binary classification problems. During each iteration, MultiTransferBoost boosted weighted instances from different source domains while each instance's weight was assigned and updated by evaluating the difficulty of the instance being correctly classified and the “transferability” of the instance's corresponding source domain to the target. The updating process repeated until it reached the predefined training error or iteration number. The weight update factors, which were analyzed and adjusted to minimize the Hamming loss of the output coding, strengthened the connections among the sub binary problems during each iteration. Experimental results demonstrated that MultiTransferBoost had better classification performance and less computational burden than existing instance-based algorithms using the One-Against-One (OAO) strategy.

We propose a heuristic approximation algorithm for the 1-median problem. The 1-median problem is the problem of finding a vertex with the highest closeness centrality. Starting from a randomly selected vertex, our algorithm repeats to find a vertex with higher closeness centrality by approximately calculating closeness centrality of each vertex using simpler spanning subgraphs, which are called k-neighbor dense shortest path graphs with shortcuts. According to our experimental results using real networks with more than 10,000 vertices, our algorithm is more than 100 times faster than the exhaustive search and more than 20 times faster than the state-of-the-art approximation algorithm using annotated information to the vertices while the solutions output by our algorithm have higher approximation ratio.

We present a lifting-based lapped transform (L-LT) and a reversible symmetric extension (RSE) in the boundary processing for more effective lossy-to-lossless image coding of data with various qualities from only one piece of lossless compressed data. The proposed dual-DCT-lifting-based LT (D2L-LT) parallel processes two identical LTs and consists of 1-D and 2-D DCT-liftings which allow the direct use of a DCT matrix in each lifting coefficient. Since the DCT-lifting can utilize any existing DCT software or hardware, it has great potential for elegant implementations that are dependent on the architecture and DCT algorithm used. In addition, we present an improved RSE (IRSE) that works by recalculating the boundary processing and solves the boundary problem that the DCT-lifting-based L-LT (DL-LT) has. We show that D2L-LT with IRSE mostly outperforms conventional L-LTs in lossy-to-lossless image coding.

In this paper, we propose a non-cooperative line-of-sight (LOS)/non-LOS channel identification algorithm with single node channel measurements based on time-of-arrival statistics. In order to improve the accuracy of channel identification, we adopt a recalibration interval in terms of measured distance to the proposed algorithm. Experimental results are presented in terms of identification probability and recalibration interval. The proposed algorithm involves a trade-off between the channel identification quality and the recalibration rate. However, depending on the recalibration interval, it is possible to greatly improve the sensitivity of the channel identification system.

The development of smart devices has led to the growth of Location-Based Social Networking Services (LBSNSs). In this paper, we introduce an l-Close Range Friends query that finds all l-hop friends of a user within a specified range. We also propose a query processing method on Social Grid Index (SGI). Using real datasets, the performance of our method is evaluated.

Using a matrix approach based on a Markov process, we investigate the reliability of a circular connected-(1,2)-or-(2,1)-out-of-(m,n):F lattice system for the i.i.d. case. We develop a modified linear lattice system that is equivalent to this circular system, and propose a methodology that allows the systematic calculation of the reliability. It is based on ideas presented by Fu and Hu [6]. A partial transition probability matrix is used to reduce the computational complexity of the calculations, and closed formulas are derived for special cases.

In this letter, efficient closed-form formulas for the exact and asymptotic average bit error probability (ABEP) of space shift keying (SSK) systems are derived over Rayleigh fading channels with imperfect channel state information (CSI). Specifically, for a generic 2×NR multiple-input multiple-output (MIMO) system with the maximum likelihood (ML) detection, the impact of imperfect CSI is taken into consideration in terms of two types of channel estimation errors with the fixed variance and the variance as a function of the number of pilot symbols and signal-to-noise ratio (SNR). Then, the explicit evaluations of the bit error floor (BEF) and asymptotic SNR loss are carried out based on the derived asymptotic ABEP formula, which accounts for the impact of imperfect CSI on the SSK system. The numerical results are presented to validate the exactness of our theoretical analysis.

Multi-view video streaming plays an important role in new interactive and augmented video applications such as telepresence, remote surgery, and entertainment. For those applications, interactive multi-view video transmission schemes have been proposed that aim to reduce the amount of video traffic. Specifically, these schemes only encode and transmit video frames, which are potentially displayed by users, based on periodical feedback from the users. However, existing schemes are vulnerable to frame loss, which often occurs during transmissions, because they encode most video frames using inter prediction and inter-view prediction to reduce traffic. Frame losses induce significant quality degradation due to the collapse of the decoding operations. To improve the loss resilience, we propose an encoding/decoding system, Frame Popularity-based Multi-view Video Streaming (FP-MVS), for interactive multi-view video streaming services. The main idea of FP-MVS is to assign intra (I) frames in the prediction structure for less/more popular (i.e., few/many observed users) potential frames in order to mitigate the impact of a frame loss. In addition, FP-MVS utilizes overlapping and non-overlapping areas between all user's potential frames to prevent redundant video transmission. Although each intra-frame has a large data size, the video traffic can be reduced within a network constraint by combining multicast and unicast for overlapping and non-overlapping area transmissions. Evaluations using Joint Multi-view Video Coding (JMVC) demonstrated that FP-MVS achieves higher video quality even in loss-prone environments. For example, our scheme improves video quality by 11.81dB compared to the standard multi-view video encoding schemes at the loss rate of 5%.

In general, Transmission Control Protocol (TCP), e.g., TCP NewReno, considers all losses to be a sign of congestion. It decreases the sending rate whenever a loss is detected. Integrating the network coding (NC) into protocol stack and making it cooperate with TCP (TCP/NC) would provide the benefit of masking packet losses in lossy networks, e.g., wireless networks. TCP/NC complements the packet loss recovery capability without retransmission at a sink by sending the redundant combination packets which are encoded at the source. However, TCP/NC is less effective under heavy and bursty loss which often occurs in fast fading channel because the retransmission mechanism of the TCP/NC entirely relies on the TCP layer. Our solution is TCP/NC with enhanced retransmission (TCP/NCwER), for which a new retransmission mechanism is developed to retransmit more than one lost packet quickly and efficiently, to allow encoding the retransmitted packets for reducing the repeated losses, and to handle the dependent combination packets for avoiding the decoding failure. We implement and test our proposal in Network Simulator 3. The results show that TCP/NCwER overcomes the deficiencies of the original TCP/NC and improves the TCP goodput under both random loss and burst loss channels.

This paper studies H∞ control for networked control systems with packet loss. In networked control systems, packet loss is one of major weakness because the control performance deteriorates due to packet loss. H∞ control, which is one of robust control, can design a controller to reduce the influence of disturbances acting on the controlled object. This paper proposes an H∞ control design that considers packet loss as a disturbance. Numerical examples show that the proposed H∞ control design can more effectively reduce control performance deterioration due to packet loss than the conventional H∞ control design. In addition, this paper provides control performance comparisons of H∞ control and Linear Quadratic (LQ) control. Numerical examples show that the control performance of the proposed H∞ control design is better than that of the LQ control design.

This paper proposed that a path loss model for outdoor-to-indoor corridor is presented to construct next generation mobile communication systems. The proposed model covers the frequency range of millimeter wave bands up to 40GHz and provides three dimensional incident angle characteristics. Analysis of path loss characteristics is conducted by ray tracing. We clarify that the paths reflected multiple times between the external walls of buildings and then diffracted into one of the buildings are dominant. Moreover, we also clarify how the paths affect the path loss dependence on frequency and three dimensional incident angle. Therefore, by taking these dependencies into consideration, the proposed model decreases the root mean square errors of prediction results to within about 2 to 6dB in bands up to 40GHz.

In many multimedia applications, image encryption has to be conducted prior to image compression. This letter proposes an Encryption-then-Compression system using JPEG XR/JPEG-LS friendly perceptual encryption method, which enables to be conducted prior to the JPEG XR/JPEG-LS standard used as an international standard lossless compression method. The proposed encryption scheme can provides approximately the same compression performance as that of the lossless compression without any encryption. It is also shown that the proposed system consists of four block-based encryption steps, and provides a reasonably high level of security. Existing conventional encryption methods have not been designed for international lossless compression standards, but for the first time this letter focuses on applying the standards.

Recently, computer speed and memory capacity have been advanced. Therefore, applicable space size or equivalently the frequency in the FDTD method has been increased similar as the ray-tracing method for radio wave propagation. The ray-tracing method can obtain easily important parameters such as path loss, delay profile and angular profile. On the other hand, the FDTD method seems difficult to obtain an angular profile. We can overcome this problem by applying the DOA estimation method to the FDTD method. In this paper, we show that the FDTD method can be used as a counterpart of the ray-tracing method to analyze radio wave propagation of large space by using DOA estimation method such as MUSIC method.

We treat lossless fixed-to-variable length source coding under general sources for finite block length setting. We evaluate the threshold of the overflow probability for prefix and non-prefix codes in terms of the smooth max-entropy. We clarify the difference of the thresholds between prefix and non-prefix codes for finite block length. Further, we discuss our results under the asymptotic block length setting.

Average coding rate of a multi-shot Tunstall code, which is a variation of variable-to-fixed length (VF) lossless source codes, for stationary memoryless sources is investigated. A multi-shot VF code parses a given source sequence to variable-length blocks and encodes them to fixed-length codewords. If we consider the situation that the parsing count is fixed, overall multi-shot VF code can be treated as a one-shot VF code. For this setting of Tunstall code, the compression performance is evaluated using two criterions. The first one is the average coding rate which is defined as the codeword length divided by the average block length. The second one is the expectation of the pointwise coding rate. It is proved that both of the above average coding rate converge to the entropy of a stationary memoryless source under the assumption that the geometric mean of the leaf counts of the multi-shot Tunstall parsing trees goes to infinity.

A generalization of compression via substring enumeration (CSE) for k-th order Markov sources with a finite alphabet is proposed, and an upper bound of the codeword length of the proposed method is presented. We analyze the worst case maximum redundancy of CSE for k-th order Markov sources with a finite alphabet. The compression ratio of the proposed method asymptotically converges to the optimal one for k-th order Markov sources with a finite alphabet if the length n of a source string tends to infinity.

This letter investigates transmit optimization in multi-user multi-input multi-output (MIMO) wiretap channels. In particular, we address the transmit covariance optimization for an artificial-noise (AN)-aided secrecy rate maximization (SRM) when subject to individual harvested energy and average transmit power. Owing to the inefficiency of the conventional interior-point solvers in handling our formulated SRM problem, a custom-designed algorithm based on penalty function (PF) and projected gradient (PG) is proposed, which results in semi-closed form solutions. The proposed algorithm achieves about two orders of magnitude reduction of running time with nearly the same performance comparing to the existing interior-point solvers. In addition, the proposed algorithm can be extended to other power-limited transmit design problems. Simulation results demonstrate the excellent performance and high efficiency of the algorithm.

The segmentation of Mycobacterium tuberculosis images forms the basis for the computer-aided diagnosis of tuberculosis. The segmented objects are often broken due to the low-contrast objects and the limits of segmentation method. This will result in decreasing the accuracy of segmentation and recognition. A simple and effective post-processing method is proposed to connect the broken objects. The broken objects in the segmented binary images are connected based on the information obtained from their skeletons. Experimental results demonstrate the effectiveness of our proposed method.

There are often low contrast Mycobacterium tuberculosis (MTB) objects in the MTB images. Based on improved histogram equalization (HE), a framework of contrast enhancement is proposed to increase the contrast of MTB images. Our proposed algorithm was compared with the traditional HE and the weighted thresholded HE. The experimental results demonstrate that our proposed algorithm has better performance in contrast enhancement, artifacts suppression, and brightness preserving for MTB images.

This paper proposes an efficient lossless coding scheme for color video in RGB 4:4:4 format. For the R signal that is encoded before the other signals at each frame, we employ a block-adaptive prediction technique originally developed for monochrome video. The prediction technique used for the remaining G and B signals is extended to exploit inter-color correlations as well as inter- and intra-frame ones. In both cases, multiple predictors are adaptively selected on a block-by-block basis. For the purpose of designing a set of predictors well suited to the local properties of video signals, we also explore an appropriate setting for the spatiotemporal partitioning of a video volume.