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.

Broadcasting is an essential function in almost all wireless networks. Because of the dynamic nature of environment, broadcasting in cognitive radio ad hoc networks is a great challenge. Cognitive radio network technology has been well studied for more than a decade as a new way to improve the spectral efficiency of wireless networks and numerous precious works have been proposed. However, very few existing works consider how to broadcast messages in cognitive radio networks that operate in multichannel environments and none of these provides a full broadcast mechanism. Therefore, in this paper, we propose a broadcasting mechanism for multichannel cognitive radio ad hoc networks. Then, we analyze the mechanism regarding the speed of message dissemination, number of transmissions, fraction of the users that receive the broadcast message and so forth.

In communication networks, congestion control, routing, and multiple access schemes for scheduling transmissions are typically regulated by distributed algorithms. Engineers designed these algorithms using clever heuristics that they refined in the light of simulation results and experiments. Over the last two decades, a deeper understanding of these algorithms emerged through the work of researchers. This understanding has a real potential for improving the design of protocols for data centers, cloud computing, and even wireless networks. Since protocols tend to be standardized by engineers, it is important that they become familiar with the insights that emerged in research. We hope that this paper might appeal to practitioners and make the research results intuitive and useful. The methods that the paper describes may be useful for many other resource allocation problems such as in call centers, manufacturing lines, hospitals and the service industry.

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.

In secret sharing scheme, Tompa and Woll considered a problem of cheaters who try to make another participant reconstruct an invalid secret. Later, some models of such cheating were formalized and lower bounds of the size of shares were shown in the situation of fixing the minimum successful cheating probability. Under the assumption that cheaters do not know the distributed secret, no efficient scheme is known which can distribute bit strings. In this paper, we propose an efficient scheme for distributing bit strings with an arbitrary access structure. When distributing a random bit string with threshold access structures, the bit length of shares in the proposed scheme is only a few bits longer than the lower bound.

We consider the minimum feedback vertex set problem for some bipartite graphs and degree-constrained graphs. We show that the problem is linear time solvable for bipartite permutation graphs and NP-hard for grid intersection graphs. We also show that the problem is solvable in O(n2log 6n) time for n-vertex graphs with maximum degree at most three.

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.

This paper proposes a visual secret sharing (VSS) scheme with efficient pixel expansion which prevents malicious share holders from deceiving an honest share holder. A VSS scheme encrypts a secret image into pieces referred to as shares where each party keeps a share so that stacking a sufficient number of shares recovers the secret image. A cheat prevention VSS scheme gives another piece to each party for verifying whether the share presented by another party is genuine. The proposed scheme improves the contrast of the recovered image and cheat-prevention functionality by introducing randomness in producing pieces for verification. Experimental results show the effectiveness of the proposed scheme.

Many EMD-type data hiding schemes have been proposed. However, the data hiding capacity is less than 2bpp when the embedding procedure uses formula operations. In order to improve the data hiding capacity from 1bpp to 4.5bpp, a new data hiding scheme is proposed in this paper based on a formula using the fully exploiting modification directions method (FEMD). By using our proposed theorem, the secret data can be embedded by formula operations directly without using a lookup matrix. The simulation results and performance analysis show the proposed scheme not only maintains good embedding capacity and stegoimage quality but also solves the overflow problem. It does so without using extra memory resources and performs within a reasonable computing time. The resource usage and capabilities of this scheme are well matched to the constraints and requirements of resource-scarce mobile devices.

A directional lapped orthogonal transform (DirLOT) is an orthonormal transform of which basis is allowed to be anisotropic with the symmetric, real-valued and compact-support property. Due to its directional property, DirLOT is superior to the existing separable transforms such as DCT and DWT in expressing diagonal edges and textures. The goal of this paper is to enhance the ability of DirLOT further. To achieve this goal, we propose a novel image restoration technique using multiple DirLOTs. This paper generalizes an image denoising technique in [1], and expands the application of multiple DirLOTs by introducing linear degradation operator P. The idea is to use multiple DirLOTs to construct a redundant dictionary. More precisely, the redundant dictionary is constructed as a union of symmetric orthonormal discrete wavelet transforms generated by DirLOTs. To select atoms fitting a target image from the dictionary, we formulate an image restoration problem as an l1-regularized least square problem, which can efficiently be solved by the iterative-shrinkage/thresholding algorithm (ISTA). The proposed technique is beneficial in expressing multiple directions of edges/textures. Simulation results show that the proposed technique significantly outperforms the non-subsampled Haar wavelet transform for deblurring, super-resolution, and inpainting.

In wireless sensor networks, energy depletion of bottleneck nodes which have more data packets to relay than others, dominates the network lifetime referred to as the funnel effect problem. To overcome this problem, multiple sink methods have been proposed where sensor nodes send observed data packets toward several sinks to distribute traffic load of bottleneck nodes. If both of the topology and the traffic pattern are symmetric, bottleneck nodes are located near sinks. However, in a general sensor network with an asymmetric topology and/or an asymmetric traffic pattern, bottleneck nodes may exist any place in the network. In this paper, we propose DCAM (DispersiveCast of packets to Avoid bottleneck nodes for Multiple sink sensor network), which is a load balancing method to improve lifetime of a sensor network with an asymmetric topology and an asymmetric traffic pattern. DCAM first finds bottleneck nodes, and then balances the load on the bottleneck nodes. Selected nodes send data packets to several sinks dispersively according to some criteria. The criteria classify DCAM into three variations: DCAM with probability (DCAM-P), DCAM with moving boarder (DCAM-MB), and DCAM with round-robin (DCAM-RR). This paper gives details of the DCAM methods, and thereafter evaluates them with asymmetric topologies and asymmetric traffic patterns. To deal with these dynamic asymmetry, the topology is modeled by a grid network with virtual holes that are defined as vacant places of nodes in the network. Asymmetry of traffic pattern is modeled by defining a hot area where nodes have heavier data traffic than the others. The evaluations are conducted as changing hot-area traffic patterns as well as fixing hot-area patterns. The results show that DCAM improves network lifetime up to 1.87 times longer than the conventional schemes, (i.e., nearest sink transmissions and optimal dispersive cast of packet). We also discuss DCAM on several aspects such as overhead, energy consumption, and applications.

This letter deals with blind carrier frequency offset estimation by exploiting the minimum variance distortionless response (MVDR) criterion for interleaved uplink orthogonal frequency division multiple access (OFDMA). It has been shown that the complexity and estimation accuracy of MVDR strictly depend on the grid size used during the search. For the purpose of efficient estimation, we present an improved polynomial rooting estimator that is robust in low signal-to-noise ratio scenario. Simulation results are provided for illustrating the effectiveness of the proposed estimator.

This paper proposes a new double-edge-triggered implicitly level-converting flip-flop, suitable for a low-power and low-voltage design. The design employs a sense amplifier architecture to reduce the delay and power consumption. Experimentally, when implemented with a 130-nm, single-Vt and 0.84V VDD process, it achieves 64% power-delay product (PDP) improvement, and moreover, 78% PDP improvement when implemented with a mixed-Vt technology, as compared to that of the classic double-edge-triggered flip-flop design.

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.

This paper presents a DC output voltage-boosting antenna with high input impedance in wide frequency band for RF (radio frequency) energy harvesting of FM broadcasting signals. Target input power level of -20dBm is used to design a loop antenna for DC output voltage-boosting. The RF energy harvesting on YNU campus provides 924mV DC output for a single rectenna and 1.72V DC output for twin rectennas by receiving several FM broadcasting wave simultaneously.

An S-band GaN on Si based 1kW-class SSPA system for space wireless applications is proposed. Since high-efficiency and high-reliability amplifier is one of the most important technologies for power and communication systems in a future space base station on a planet, compact, high-power, and high-efficiency SSPA is strongly requested instead of TWTA. Thus, we adopt GaN on Si based amplifier due to its remarkable material properties. At the beginning, thermal vacuum and radiation test of GaN on Si are conducted so as to confirm the space applicability. Fabricated SSPA system consists of eight 200W HPAs and coaxial waveguide power combiner. It achieves high efficiency such as 57% of drain efficiency and 87% of combining efficiency when RF output power achieves more than 60dBm. Furthermore, long-term stable operation and good phase noise characteristics are also confirmed.

In this paper, we propose a use of the group sparsity in adaptive learning of second-order Volterra filters for the nonlinear acoustic echo cancellation problem. The group sparsity indicates sparsity across the groups, i.e., a vector is separated into some groups, and most of groups only contain approximately zero-valued entries. First, we provide a theoretical evidence that the second-order Volterra systems tend to have the group sparsity under natural assumptions. Next, we propose an algorithm by applying the adaptive proximal forward-backward splitting method to a carefully designed cost function to exploit the group sparsity effectively. The designed cost function is the sum of the weighted group l1 norm which promotes the group sparsity and a weighted sum of squared distances to data-fidelity sets used in adaptive filtering algorithms. Finally, Numerical examples show that the proposed method outperforms a sparsity-aware algorithm in both the system-mismatch and the echo return loss enhancement.

The authors previously conducted the observation of microstructures and three-dimensional SEM on fretting wear phenomena at tin-plated contacts. In this study, we report the fretting characteristics of dissimilar metal contacts by studying the relation between the contact resistance behaviors and micro structural changes of gold and tin-plated fretting contacts, through surface SEM observations and cross sectional SEM and AES analysis.

Test power has become a critical issue, especially for low-power devices with deeply optimized functional power profiles. Particularly, excessive capture power in at-speed scan testing may cause timing failures that result in test-induced yield loss. This has made capture-safety checking mandatory for test vectors. However, previous capture-safety checking metrics suffer from inadequate accuracy since they ignore the time relations among different transitions caused by a test vector in a circuit. This paper presents a novel metric called the Transition-Time-Relation-based (TTR) metric which takes transition time relations into consideration in capture-safety checking. Detailed analysis done on an industrial circuit has demonstrated the advantages of the TTR metric. Capture-safety checking with the TTR metric greatly improves the accuracy of test vector sign-off and low-capture-power test generation.

The authors have developed a mechanism that applies real vibration to electrical contacts by hammering oscillation in the vertical direction similar to that in real cases, and they have studied the effects of micro-oscillation on the contacts using the mechanism. It is shown that the performance of the hammering oscillation mechanism (HOM) for measuring acceleration and force is superior to that of other methods in terms of the stability of data. Using the mechanism, much simpler and more practical protocols are proposed for evaluating acceleration, force, and mass using only the measured acceleration. It is also indicated that the relationship between the inertial force generated by the hammering oscillation mechanism and the frictional force in electrical devices attached on a board is related to one of the causes of the degradation of electrical contacts under the effect of external micro-oscillation.