In 2001, Boneh and Franklin realized the first Identity-Based Encryption (IBE), and at the same time they proposed a simple way to revoke users from the system. Later, Boldyreva et al. pointed out that Boneh-Franklin's revocation method is not scalable well and they proposed the first IBE scheme with efficient revocation. Recently, Tseng and Tsai [Computer Journal, Vol.55 No.4, page 475-486, 2012] claimed that Boldyreva et al.'s scheme requires a secure channel between each user and the key generation center in the key update phase, and proposed a new revocable IBE (RIBE) with a public channel by extending the Boneh-Franklin scheme. In this paper, we revisit Tseng and Tsai's result; we first point out that secure channels (except for the initial key setup) are not mandatory in the definition of RIBE scheme formalized by Boldyreva et al. Next, we show that Boldyreva et al.'s scheme does not require any secure channels (except for the initial key setup), which is different from what Tseng and Tsai claimed and so invalidates their contribution of the first RIBE with a public channel. Moreover, we point out that there are simple techniques to remove secure channels from the Boneh-Franklin RIBE. Interestingly, we show that the secure-channel-free Boneh-Franklin RIBE scheme is secure against decryption key exposure, whereas the Tseng-Tsai RIBE scheme is vulnerable to this attack.

Morphemes, which are obtained from morphological parsing, and statistical sub-words, which are derived from data-driven splitting, are commonly used as the recognition units for speech recognition of agglutinative languages. In this letter, we propose a discriminative approach to select the splitting result, which is more likely to improve the recognizer's performance, for each distinct word type. An objective function which involves the unigram language model (LM) probability and the count of misrecognized phones on the acoustic training data is defined and minimized. After determining the splitting result for each word in the text corpus, we select the frequent units to build a hybrid vocabulary including morphemes and statistical sub-words. Compared to a statistical sub-word based system, the hybrid system achieves 0.8% letter error rates (LERs) reduction on the test set.

The link structure of the Web is generally viewed as a webgraph. One of the main objectives of web structure mining is to find hidden communities on the Web based on the webgraph, and one of its approaches tries to enumerate substructures, each of which corresponds to a set of web pages of a community or its core. Research has shown that certain substructures can find sets of pages that are inherently irrelevant to communities. In this paper, we propose a model, which we call contracted webgraphs, where such substructures are contracted into single nodes to hide useless information. We then try structure mining iteratively on those contracted webgraphs since we can expect to find further hidden information once irrelevant information is eliminated. We also explore the structural properties of contracted webgraphs from the viewpoint of scale-freeness, and we observe that they exhibit novel and extreme self-similarities.

Source routing multicast has been gathering much more attention rather than traditional IP multicast, since it is thought to be more scalable in terms of the number of groups at the cost of higher traffic loads. This paper introduces a mathematical framework to analyze the scalability of source routing multicast and IP multicast by leveraging previous multicast studies. We first analyze the amount of data traffic based on the small-world nature of networks, and show that source routing multicast can be as efficient as IP multicast if a simple header fragmentation technique (subgrouping) is utilized. We also analyze scalability in terms of group numbers, which are derived under the equal budget assumption. Our analysis shows that source routing multicast is competitive for low bit-rate streams, like those in the publish/subscribe service, but we find some factors that offset the advantage. This is the first work to analytically investigate the scalability of source routing multicast.

As an extension of H.264/AVC, Scalable Video Coding (SVC) provides the ability to adapt to heterogeneous networks and user-end requirements, which offers great scalability in multi-point applications such as videoconferencing. However, transcoding between SVC and AVC becomes necessary due to the existence of legacy AVC-based systems. The straightforward full re-encoding method requires great computational cost, and the fast SVC-to-AVC spatial transcoding techniques have not been thoroughly investigated yet. This paper proposes a low-complexity hybrid-domain SVC-to-AVC spatial transcoder with drift compensation, which provides even better coding efficiency than the full re-encoding method. The macroblocks (MBs) of input SVC bitstream are divided into two types, and each type is suitable for pixel- or transform-domain processing respectively. In the pixel-domain transcoding, a fast re-encoding method is proposed based on mode mapping and motion vector (MV) refinement. In the transform-domain transcoding, the quantized transform coefficients together with other motion data are reused directly to avoid re-quantization loss. The drift problem caused by proposed transcoder is solved by compensation techniques for I frame and P frame respectively. Simulation results show that proposed transcoder achieves averagely 96.4% time reduction compared with the full re-encoding method, and outperforms the reference methods in coding efficiency.

Electromagnetic scattering and radiation in cylindrical electromagnetic bandgap (EBG) structure is analyzed. The radiated field from a line source placed inside the eccentric configuration of the cylindrical EBG structure and plane wave incident on the cylindrical EBG structure is numerically studied based on the method proposed by the authors in their early papers. Using the developed formulation, it is shown first time that when the cylindrical EBG is illuminated by plane wave of particular resonance frequencies, the field are strongly enhanced or shaded inside the cylindrical EBG structure and this effect depends on the angle of incidence of the plane waves. We give a deep physical insight into explanation of this phenomenon based on the Lorentz reciprocity relation for cylindrical structures.

We propose a natural synchronization scheme for wireless uncoupled devices, without any signal exchange among them. Our proposed scheme only uses natural environmental fluctuations, such as the temperature or humidity of the air, the environmental sounds, and so on, for the synchronization of the uncoupled devices. This proposed synchronization is realized based on the noise-induced synchronization phenomenon, uncoupled nonlinear oscillators synchronize with each other only by adding identical common noises to each of them. Based on the theory of this phenomenon, the oscillators can also be synchronized by noise sequences, which are not perfectly identical signals. Since the environmental natural fluctuations collected at neighboring locations are similar to each other and cross-correlation becomes high, our proposed scheme enabling synchronization only by natural environmental fluctuations can be realized. As an application of this proposed synchronization, we introduce wireless sensor networks, for which synchronization is important for reducing power consumption by intermittent data transmission. We collect environmental fluctuations using the wireless sensor network devices. Our results show that the wireless sensor network devices can be synchronized only by the independently collected natural signals, such as temperature and humidity, at each wireless sensor device.

Recently, many kinds of content are being circulated within a great many service-specific overlay networks. When the content is not extremely delay-sensitive, content circulation between wireless terminals can be realized without additional resources by using off-peak periods in wireless access links. In such content circulation, peer-to-peer content multicast is a promising approach to reduce the load on the centralized server. However, to minimize battery drain, each wireless terminal can only forward content to a restricted number of neighboring terminals once it has received the content. This paper proposes an efficient forwarding scheme for peer-to-peer content multicast between the wireless terminals intermittently connected with the backhaul network. In the proposed scheme, a restricted number of terminals with an earlier start time of off-peak periods are selected to forward the content when the number of forwarding hops from the source terminal is less than or equal to a predetermined threshold. In contrast, a restricted number of terminals are selected randomly when the number of forwarding hops exceeds the threshold. This paper clarifies that the proposed hybrid forwarding scheme can multicast the content to many terminals within an arbitrarily restricted period. A guideline to determine the optimum threshold for switching the terminal selection method in the proposed hybrid scheme is derived from simulation results.

This paper presents a new scalable method to considerably reduce the rollback propagation effect of the conventional optimistic message logging by utilizing positive features of reliable FIFO group communication links. To satisfy this goal, the proposed method forces group members to replicate different receive sequence numbers (RSNs), which they assigned for each identical message to their group respectively, into their volatile memories. As the degree of redundancy of RSNs increases, the possibility of local recovery for each crashed process may significantly be higher. Experimental results show that our method can outperform the previous one in terms of the rollback distance of non-faulty processes with a little normal time overhead.

In this paper, we propose a jointly optimized predictive-adaptive partitioned block transform to exploit the spatial characteristics of intra residuals and improve video coding performance. Under the assumptions of traditional Markov representations, the asymmetric discrete sine transform (ADST) can be combined with a discrete cosine transform (DCT) for video coding. In comparison, the interpolative Markov representation has a lower mean-square error for images or regions that have relatively high contrast, and is insensitive to changes in image statistics. Hence, we derive an even discrete sine transform (EDST) from the interpolative Markov model, and use a coding scheme to switch between EDST and DCT, depending on the prediction direction and boundary information. To obtain an implementation independent of multipliers, we also propose an orthogonal 4-point integer EDST, which consists solely of adds and bit-shifts. We implement our hybrid transform coding scheme within the H.264/AVC intra-mode framework. Experimental results show that the proposed scheme significantly outperforms standard DCT and ADST. It also greatly reduces the blocking artifacts typically observed around block edges, because the new transform is more adaptable to the characteristics of intra-prediction residuals.

This paper describes a robust three-dimensional (3D) surface reconstruction method that can automatically eliminate shadowing errors. For modeling shadowing effect, a new shadowing compensation model based on the angle distribution of backscattered electrons is introduced. Further, it is modified with respect to some practical factors. Moreover, the proposed iterative shadowing compensation method, which performs commutatively between the compensation of image intensities and the modification of the corresponding 3D surface, can effectively provide both an accurate 3D surface and compensated shadowless images after convergence.

To raise the energy efficiency of wireless clients, it is important to sleep in idle periods. When multiple network applications are running concurrently on a single wireless client, packets of each application are sent and received independently, but multiplexed at MAC-level. This uncoordinated behavior makes it difficult to control of sleep timing. In addition, frequent state transitions between active and sleep modes consume non-negligible energy. In this paper, we propose a transport-layer approach that resolves this problem and so reduces energy consumed by multiple TCP flows on a wireless LAN (WLAN) client. The proposed method, called SCTP tunneling, has two key features: flow aggregation and burst transmission. It aggregates multiple TCP flows into a single SCTP association between a wireless client and an access point to control packet transmission and reception timing. Furthermore, to improve the sleep efficiency, SCTP tunneling reduces the number of state transitions by handling multiple packets in a bursty fashion. In this study, we construct a mathematical model of the energy consumed by SCTP tunneling to assess its energy efficiency. Through numerical examples, we show that the proposed method can reduce energy consumption by up to 69%.

This paper reviews two simple numerical algorithms particularly useful in Computational ElectroMagnetics (CEM): the Weighted Averages (WA) algorithm and the Double Exponential (DE) quadrature. After a short historical introduction and an elementary description of the mathematical procedures underlying both techniques, they are applied to the evaluation of Sommerfeld integrals, where WA and DE combine together to provide a numerical tool of unprecedented quality. It is also shown that both algorithms have a much wider range of applications. A generalization of the WA algorithm, able to cope with integrands including products of Bessel and similar oscillatory functions, is described. Similarly, the original DE algorithm is adapted with exceptional results to the evaluation of the multidimensional singular integrals arising in the discretization of Integral-Equation based CEM formulations. The new possibilities of WA and DE algorithms are demonstrated through several practical numerical examples.

A novel spatially modulated communication method, appropriate for wireless power transmission applications at 5.8GHz, is proposed using dual scatterers embedded with lumped elements. Analytical expression for the received wave in the spatial modulation is derived, and the characteristics are verified with simulation and measurement by varying the embedded capacitor. The maximum measured variation of the received voltage is more than 15dB and that of the phase is more than 270 degrees at 5.8GHz. The estimated amplitude modulation factor is more than 70%. Using the data obtained, we estimate the practical received waveforms modulated by the applied voltage to a varactor for the amplitude modulation scheme.

In this paper, a 24GHz transformer-coupled VCO is presented for a wide linear tuning range in the 0.13-µm CMOS process. The measured results of the proposed VCO show that the center frequency is 23.5GHz with 7.4% frequency tuning range. The output frequency curve has wide linear tuning region (5.5%) at the middle of the curve. Also, the VCO exhibits good phase noise of -110.23dBc/Hz at an offset frequency of 1 MHz. It has a compact chip size of 430 × 500µm2. The VCO core DC power consumption is 5.4mW at 1.35V VDD.

In this letter, a fast transmit antenna selection algorithm is proposed for the spatial-temporal combining-based spatial multiplexing ultra-wideband systems on a log-normal multipath fading channel. The presented suboptimum algorithm selects the transmit antennas associated with the largest signal to noise ratio value computed by one QR decomposition operation of the full channel matrix spatially and temporally combined. It performs the iterative channel scaling operation about the channel matrix and singular value decomposition about the channel scaled matrix. It is shown that the proposed antenna selection algorithm leads to a substantial improvement in the error performance while keeping low-complexity, and obtains almost the same error performance as the exhaustive search-based optimal antenna selection algorithm.

By exploiting data-level parallelism, Graphics Processing Units (GPUs) have become a high-throughput, general purpose computing platform. Many real-world applications especially those following a stream processing pattern, however, feature interleaved task-pipelined and data parallelism. Current GPUs are ill equipped for such applications due to the insufficient usage of computing resources and/or the excessive off-chip memory traffic. In this paper, we focus on microarchitectural enhancements to enable task-pipelined execution of data-parallel kernels on GPUs. We propose an efficient adaptive dynamic scheduling mechanism and a moderately modified L2 design. With minor hardware overhead, our techniques orchestrate both task-pipeline and data parallelisms in a unified manner. Simulation results derived by a cycle-accurate simulator on real-world applications prove that the proposed GPU microarchitecture improves the computing throughput by 18% and reduces the overall accesses to off-chip GPU memory by 13%.

To handle the variety of scene characters, we propose a cooperative multiple-hypothesis framework which consists of an image operator set module, an Optical Character Recognition (OCR) module and an integration module. Multiple image operators activated by multiple parameters probe suspected character regions. The OCR module is then applied to each suspected region and returns multiple candidates with weight values for future integration. Without the aid of the heuristic rules which impose constraints on segmentation area, aspect ratio, color consistency, text line orientations, etc., the integration module automatically prunes the redundant detection/recognition and pads the missing detection/recognition. The proposed framework bridges the gap between scene character detection and recognition, in the sense that a practical OCR engine is effectively leveraged for result refinement. In addition, the proposed method achieves the detection and recognition at the character level, which enables dealing with special scenarios such as single character, text along arbitrary orientations or text along curves. We perform experiments on the benchmark ICDAR 2011 Robust Reading Competition dataset which includes a text localization task and a word recognition task. The quantitative results demonstrate that multiple hypotheses outperform a single hypothesis, and be comparable with state-of-the-art methods in terms of recall, precision, F-measure, character recognition rate, total edit distance and word recognition rate. Moreover, two additional experiments are conducted to confirm the simplicity of parameter setting in this proposal.

Metamaterials are generally defined as a class of artificial effective media which macroscopically exhibit extraordinary electromagnetic properties that may not be found in nature, and are composed of periodically structured dielectric, or magnetic, or metallic materials. This paper reviews recently developed electromagnetic modeling methods of metamatericals and their inherent basic ideas, with a focus on full wave numerical techniques. Methods described in this paper are the Method of Moments (MoM) and the Finite Difference Time Domain (FDTD) Method for scattering problems excited by an incident plane wave and a single nonperiodic source, and the Finite Element Method (FEM), the Finite Difference Frequency Domain (FDFD) method and the FDTD method for band diagram calculations.

A wideband on-body antenna for a wireless body area network for an Industrial, Scientific, and Medical band is proposed. A wideband characteristic is achieved by combining two zeroth-order resonance (ZOR) modes at adjacent frequencies by controlling the value of the shunt capacitance. The size of the proposed antenna is 0.072λ0 × 0.33λ0, and the measured 10-dB return loss bandwidth is 340MHz (14.3%). In addition, the resonance frequencies operating in the ZOR mode are insensitive to the effects of the human body by virtue of the ZOR characteristic.