For the last few decades, learning with multiple kernels, represented by the ensemble kernel regressor and the multiple kernel regressor, has attracted much attention in the field of kernel-based machine learning. Although their efficacy was investigated numerically in many works, their theoretical ground is not investigated sufficiently, since we do not have a theoretical framework to evaluate them. In this paper, we introduce a unified framework for evaluating kernel regressors with multiple kernels. On the basis of the framework, we analyze the generalization errors of the ensemble kernel regressor and the multiple kernel regressor, and give a sufficient condition for the ensemble kernel regressor to outperform the multiple kernel regressor in terms of the generalization error in noise-free case. We also show that each kernel regressor can be better than the other without the sufficient condition by giving examples, which supports the importance of the sufficient condition.

This paper analyzes the impact of directional antennas in improving the transmission capacity, defined as the maximum allowable spatial node density of successful transmissions multiplied by their data rate with a given outage constraint, in wireless networks. We consider the case where the gain Gm for the mainlobe of beamwidth can scale at an arbitrarily large rate. Under the beamwidth scaling model, the transmission capacity is analyzed for all path-loss attenuation regimes for the following two network configurations. In dense networks, in which the spatial node density increases with the antenna gain Gm, the transmission capacity scales as Gm4/α, where α denotes the path-loss exponent. On the other hand, in extended networks of fixed node density, the transmission capacity scales logarithmically in Gm. For comparison, we also show an ideal antenna model where there is no sidelobe beam. In addition, computer simulations are performed, which show trends consistent with our analytical behaviors. Our analysis sheds light on a new understanding of the fundamental limit of outage-constrained ad hoc networks operating in the directional mode.

This paper studies a privacy-preserving decision tree learning protocol (PPDT) for vertically partitioned datasets. In vertically partitioned datasets, a single class (target) attribute is shared by both parities or carefully treated by either party in existing studies. The proposed scheme allows both parties to have independent class attributes in a secure way and to combine multiple class attributes in arbitrary boolean function, which gives parties some flexibility in data-mining. Our proposed PPDT protocol reduces the CPU-intensive computation of logarithms by approximating with a piecewise linear function defined by light-weight fundamental operations of addition and constant multiplication so that information gain for attributes can be evaluated in a secure function evaluation scheme. Using the UCI Machine Learning dataset and a synthesized dataset, the proposed protocol is evaluated in terms of its accuracy and the sizes of trees*.

In many multimedia applications, image encryption has to be conducted prior to image compression. This paper proposes a JPEG-friendly perceptual encryption method, which enables to be conducted prior to JPEG and Motion JPEG compressions. The proposed encryption scheme can provides approximately the same compression performance as that of JPEG compression without any encryption, where both gray scale images and color ones are considered. It is also shown that the proposed scheme consists of four block-based encryption steps, and provide a reasonably high level of security. Most of conventional perceptual encryption schemes have not been designed for international compression standards, but this paper focuses on applying the JPEG and Motion JPEG standards, as one of the most widely used image compression standards. In addition, this paper considers an efficient key management scheme, which enables an encryption with multiple keys to be easy to manage its keys.

The technique of partial transmit sequences (PTS) is effective in reducing the peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signals. However, the conventional PTS (CPTS) scheme has high computation complexity because it needs several inverse fast Fourier transform (IFFT) units and an optimization process to find the candidate signal with the lowest PAPR. In this paper, we propose a new low-complexity PTS scheme for OFDM systems, in which a hybrid subblock partition method (SPM) is used to reduce the complexity that results from the IFFT computations and the optimization process. Also, the PAPR reduction performance of the proposed PTS scheme is further enhanced by multiplying a selected subblock with a predefined phase rotation vector to form a new subblock. The time-domain signal of the new subblock can be obtained simply by performing a circularly-shift-left operation on the IFFT output of the selected subblock. Computer simulations show that the proposed PTS scheme achieves a PAPR reduction performance close to that of the CPTS scheme with the pseudo-random SPM, but with much lower computation complexity.

A connected-(r,s)-out-of-(m,n): F system is a kind of the connected-X-out-of-(m,n): F system defined by Boehme et al. [2]. A connected-(r,s)-out-of-(m,n): F system consists of m×n components arranged in (m,n)-matrix. This system fails if and only if there exists a grid of size r×s in which all components are failed. When m=r, this system can be regarded as a consecutive-s-out-of-n: F system, and then the optimal arrangement of this system satisfies theorem which stated by Malon [9] in the case of s=2. In this study, we proposed a new algorithm for obtaining optimal arrangement of the connected-(r,2)-out-of-(m,n): F system based on the above mentioned idea. We performed numerical experiments in order to compare the proposed algorithm with the algorithm of enumeration method, and calculated the order of the computation time of these two algorithms. The numerical experiments showed that the proposed algorithm was more efficiently than the algorithm of enumeration method.

In social websites, users acquire information from adjacent neighbors as well as distant users by seeking along hyperlinks, and therefore, information diffusions, also seen as processes of “user infection”, show both cascading and jumping routes in social networks. Currently, existing analysis suffers from the difficulty in distinguishing between the impacts of information seeking behaviors, i.e. random walks, and other factors leading to user infections. To this end, we present a mechanism to recognize and measure influences of random walks on information diffusions. Firstly, we propose the concept of information propagation structure (IPS), which is also a directed acyclic graph, to represent frequent information diffusion routes in social networks. In IPS, we represent “jumping routes” as virtual arcs and regard them as the traces of random walks. Secondly, we design a frequent IPS mining algorithm (FIPS). By considering descendant node infections as a consequence of ancestor node infections in IPS, we can use a Bayesian network to model each IPS, and learn parameters based on the records of information diffusions passing through the IPS. Finally, we present a quantitative description method of random walks influence, the method is based on Bayesian probabilistic inferring in IPS, which is used to determine the ancestors, whose infection causes the infection of target users. We also employ betweenness centralities of arcs to evaluate contributions of random walks to certain infections. Experiments are carried out with real datasets and simulations. The results show random walks are influential in early and steady phases of information diffusions. They help diffusions pass through some topology limitations in social networks.

Most of the current voice conversion methods are conducted based on parallel speech, which is not easily obtained in practice. In this letter, a novel iterative speaker model alignment (ISMA) method is proposed to address this problem. First, the source and target speaker models are each trained from the background model by adopting maximum a posteriori (MAP) algorithm. Then, a novel ISMA method is presented for alignment and transformation of spectral features. Finally, the proposed ISMA approach is further combined with a Gaussian mixture model (GMM) to improve the conversion performance. A series of objective and subjective experiments are carried out on CMU ARCTIC dataset, and the results demonstrate that the proposed method significantly outperforms the state-of-the-art approach.

A novel high common-mode (CM) suppression wideband balanced passband filter (BPF) is proposed using the stub centrally loaded slotline resonators (SCLSR) which have two resonant frequencies (odd- and even-modes) in the desired passband. The odd-mode resonant frequency of the slotline SCLSR can be flexibly controlled by the stub, whereas the even-mode one is fixed. Meanwhile, a transmission zero near the odd-mode resonant frequency can be generated due to the main path signal counteraction. First, the wideband single-ended BPF and corresponding balanced BPF are designed based on the slotline SCLSR with the parallel coupled microstrip line input/output (I/O). Ultra wideband high CM suppression that can be achieved for the slotline resonator structure has no resonant mode under CM excitation. Furthermore, by folding the parallel coupled microstrip line I/O, the source-load coupling is effectively decoupled to improve the CM suppression within the passband. The high suppression wideband balanced BPF is fabricated and measured, respectively. Good agreement between simulation and measurement results is obtained.

The effect of annealing on the field emission characteristics of a field emitter comprising diamond micropowder was investigated. The threshold voltage Vth at which the emission current begins to flow decreased as the annealing temperature increased, and a minimum Vth was obtained at an annealing temperature of 1345K. The reduction in threshold voltage was due to a reduction in the work function with annealing.

We propose efficient algorithms for Sorting k-Sets in Bins. The Sorting k-Sets in Bins problem can be described as follows. We are given numbered n bins with k balls in each bin. Balls in the i-th bin are numbered n-i+1. We can only swap balls between adjacent bins. Our task is to move all of the balls to the same numbered bins. For this problem, we give an efficient greedy algorithm with $rac{k+1}{4}n^2+O(k+n)$ swaps and provide a detailed analysis for k=3. In addition, we give a more efficient recursive algorithm using $rac{15}{16}n^2+O(n)$ swaps for k=3.

In this letter we develop a software reliability modeling framework by introducing the Burr XII distributions to software fault-detection time. An extension to deal with software metrics data characterizing the product size, program complexity or testing expenditure is also proposed. Finally, we investigate the goodness-of-fit performance and compare our new models with the existing ones through real data analyses.

Recently, standard organizations of ATSC, DVB and TTA have been working to design various immersive media broadcasting services such as the hybrid network-based 3D video, UHD video and multiple views. This letter focuses on providing a new synchronization and transport system target decoder (T-STD) model of 3D video distribution based on heterogeneous transmission protocol in a hybrid network environment, where a broadcasting network and broadband (IP) network are combined. On the basis of the experimental results, the proposed technology has been proved to be successfully used as a core element for synchronization and T-STD model in a hybrid network-based 3D broadcasting. It has been also found out that it could be used as a base technique for various IP associated hybrid broadcasting services.

In this paper, we consider a distributed power control scheme that can maximize overall capacity of an interference-limited wireless system in which the same radio resource is spatially reused among different transmitter-receiver pairs. This power control scheme employs a gradient-descent method in each transmitter, which adapts its own transmit power to co-channel interference dynamically to maximize the total weighted sum rate (WSR) of the system over a given interval. The key contribution in this paper is to propose a common feedback channel, over which a backward physical signal is accumulated for computing the gradient of the transmit power in each transmitter, thereby significantly reducing signaling overhead for the distributed power control. We show that the proposed power control scheme can achieve almost 95% of its theoretical upper WSR bound, while outperforming the non-power-controlled system by roughly 63% on average.

For realizing wideband class-F power amplifiers (PA), geo-electrical analysis methods are introduced to determine the best design parameters in a simpler way than relying on computer-guided optimization. The fabricated class-F PA at 1.9 GHz demonstrated a peak efficiency of 80.5% and a bandwidth of 750 MHz for an efficiency of more than 63%. It is presumed that the optimization increased the bandwidth by 10%.

In this paper, we propose an utilization-aware hybrid beacon scheduling method for a large-scale IEEE 802.15.4 cluster-tree ZigBee network. The proposed method aims to enhance schedulability of a target network by better utilizing transmission medium, while avoiding inter-cluster collisions at the same time. To achieve this goal, the proposed scheduling method partially allows beacon overlaps, if appropriate. In particular, this paper answers for the following questions: 1) on which condition clusters can send overlapped beacons, 2) how to select clusters to overlap with minimizing utilization, and 3) how to adjust beacon parameters for grouped clusters. Also, we quantitatively evaluate the proposed method compared to previous works — i.e., non-beacon scheduling and a serialized beacon scheduling algorithm — from several aspects including total duty cycles, packet drop rate, and end-to-end delay.

Wireless sensor networks play an important role in several industries. Ad-hoc networks with multi-hop transmissions are considered suitable for wireless sensor networks because of their high scalability and low construction cost. However, a lack of centralized control makes it difficult to respond to congestion when system capacity is exceeded. Therefore, the analysis of system capacity is a critical issue for system design. In this paper, we propose a novel zone division model to analyze the capacity of multi-hop wireless sensor networks using carrier sense multiple access with collision avoidance protocols. We divide the one-hop area to a gateway (GW) into two zones: an outer zone, where access nodes (ANs) can relay packets from multi-hop ANs, and an inner zone where ANs cannot relay packets. Using this approach, we calculate the packet loss for each zone to estimate the capacity, considering the difference in the communication range of the GW and ANs, as well as the collision with hidden nodes. Comparisons with simulation results and the conventional method show that our model achieves higher estimation accuracy.

This paper proposes a rate adaptation scheme (RAS) for a wireless local area network (WLAN) station powered with microwave power transmission (MPT). A WLAN station attempting to transmit data frames when exposed to microwave radiation for MPT, experiences a reduction in the physical (PHY) layer data rate because frames are lost even when the carrier sense mechanism is used. The key idea of the proposed scheme is to utilize the output of the rectenna used for receiving microwave power. Using rectenna output, a WLAN station based on the proposed scheme assesses whether the station is exposed to microwave radiation for MPT. Then, using historical data corresponding to the assessment result, the station selects an appropriate PHY data rate. The historical data are obtained from previous transmission results, e.g., historical data pertaining to the data frame loss ratio. The proposed scheme was implemented and verified through an experiment. Experimental results showed that the proposed scheme prevents the reduction in the PHY data rate, which is caused by the use of historical data stored in a single memory. Thus, the proposed scheme leads to an improvement in the WLAN throughput.

In this paper, a new approach is proposed for extracting the spatio-temporal patterns from a location-based social networking system (SNS) such as Foursquare. The proposed approach consists of the following procedures. First, the spatio-temporal behaviors of users in SNS are approximated as a probabilistic distribution by using a diffusion-type formula. Since the SNS datasets generally consist of sparse check-in's of users at some time points and locations, it is difficult to investigate the spatio-temporal patterns on a wide range of time and space scales. The proposed method can estimate such wide range patterns by smoothing the sparse datasets by a diffusion-type formula. It is crucial in this method to estimate robustly the scale parameter by giving a prior generative model on check-in's of users. The robust estimation enables the method to extract appropriate patterns even in small local areas. Next, the covariance matrix among the time points is calculated from the estimated distribution. Then, the principal eigenfunctions are approximately extracted as the spatio-temporal patterns by principal component analysis (PCA). The distribution is a mixture of various patterns, some of which are regular ones with a periodic cycle and some of which are irregular ones corresponding to transient events. Though it is generally difficult to separate such complicated mixtures, the experiments on an actual Foursquare dataset showed that the proposed method can extract many plausible and interesting spatio-temporal patterns.

Cu-Mo alloy carries forward not only high electrical conductivity and high thermal conductivity from Cu but also high hardness from Mo, which makes it a promising potential application in electrical contact fields. In this paper, arc characteristic and erosion characteristic of Cu-Mo contacts are studied with a bridge-type contact high speed break mechanism on DC270 V/200 A load condition. And in each experiment group, 2500 times break operations are carried out. During every break operation, a high-speed AD card is used to record voltage and current signal of the arc, a high-speed camera is applied to record arcing process, and the temperature of contacts and arc are acquired by thermocouple and spectrometer, respectively. The mass and contact resistance of contacts are measured before and after every group experiment. Besides, the photograph of contact surface is taken by SEM to help analyze the erosion characteristic. The comparison between Cu-Mo contacts and Cu contacts indicates that although Cu contacts have a better electrical conductivity and thermal conductivity, Cu-Mo contacts can decrease the temperature of arc to prevent thermal breakdown, and they are also harder to be ablated and have a longer life span.