Consider a simple undirected graph G = (V,E) with vertex set V and edge set E. Let G-u be a subgraph induced by the vertex set V-{u}. The distance δG(x,y) is defined as the length of the shortest path between vertices x and y in G. The vertex u ∈ V is a hinge vertex if there exist two vertices x,y ∈ V-{u} such that δG-u(x,y)>δG(x,y). Let U be a set consisting of all hinge vertices of G. The neighborhood of u is the set of all vertices adjacent to u and is denoted by N(u). We define d(u) = max{δG-u(x,y) | δG-u(x,y)>δG(x,y),x,y ∈ N(u)} for u ∈ U as detour degree of u. A maximum detour hinge vertex problem is to find a hinge vertex u with maximum d(u) in G. In this paper, we proposed an algorithm to find the maximum detour hinge vertex on an interval graph that runs in O(n2) time, where n is the number of vertices in the graph.

Existing fault localization approaches usually do not provide a context for developers to understand the problem. Thus, this paper proposes a novel approach using the dynamic backward slicing technique to enrich contexts for existing approaches. Our empirical results show that our approach significantly outperforms five state-of-the-art fault localization techniques.

We consider the problem of optimizing the quantizer design for distributed estimation systems where all nodes located at different sites collect measurements and transmit quantized data to a fusion node, which then produces an estimate of the parameter of interest. For this problem, the goal is to minimize the amount of information that the nodes have to transmit in order to attain a certain application accuracy. We propose an iterative quantizer design algorithm that seeks to find a non-regular mapping between quantization partitions and their codewords so as to minimize global distortion such as the estimation error. We apply the proposed algorithm to a system where an acoustic amplitude sensor model is employed at each node for source localization. Our experiments demonstrate that a significant performance gain can be achieved by our technique as compared with standard typical designs and even with distributed novel designs recently published.

In this paper, we present a lattice based method on small secret exponent attack on the RSA scheme. Boneh and Durfee reduced the attack to finding the small roots of the bivariate modular equation: x(N+1+y)+1 ≡ 0 (mod e), where N is an RSA modulus and e is the RSA public key and proposed a lattice based algorithm for solving the problem. When the secret exponent d is less than N0.292, their method breaks the RSA scheme. Since the lattice used in the analysis is not full-rank, the analysis is not easy. Blömer and May proposed an alternative algorithm that uses a full-rank lattice, even though it gives a bound (d≤N0.290) that is worse than Boneh-Durfee. However, the proof for their bound is still complicated. Herrmann and May, however, have given an elementary proof for the Boneh-Durfee's bound: d≤N0.292. In this paper, we first give an elementary proof for achieving Blömer-May's bound: d≤N0.290. Our proof employs the unravelled linearization technique introduced by Herrmann and May and is rather simpler than that of Blömer-May's proof. We then provide a unified framework — which subsumes the two previous methods, the Herrmann-May and the Blömer-May methods, as a special case — for constructing a lattice that can be are used to solve the problem. In addition, we prove that Boneh-Durfee's bound: d≤N0.292 is still optimal in our unified framework.

This paper studies Tripartite Key Exchange (3KE) which is a special case of Group Key Exchange. Though general one-round GKE satisfying advanced security properties such as forward secrecy and maximal-exposure-resilience (MEX-resilience) is not known, it can be efficiently constructed with the help of pairings in the 3KE case. In this paper, we introduce the first one-round 3KE which is MEX-resilient in the standard model, though existing one-round 3KE schemes are proved in the random oracle model (ROM), or not MEX-resilient. Each party broadcasts 4 group elements, and executes 14 pairing operations. Complexity is only three or four times larger in computation and communication than the existing most efficient MEX-resilient 3KE scheme in the ROM; thus, our protocol is adequately practical.

In this paper, we consider decouple-and-forward (DCF) relaying, where the relay encodes and amplifies decoupled data using orthogonal space-time block codes (OSTBCs), to achieve the maximum diversity gain of multiple-input multiple-output (MIMO) amplify-and-forward (AF) relaying. Since the channel status of all antennas is generally unknown and time-varying for cooperation in multi-antenna multiple-relay systems, we investigate an opportunistic relaying scheme for DCF relaying to harness distributed antennas and minimize the cooperation overheads by not using the global channel state information (CSI). In addition, for realistic wireless channels which have spatial fading correlation due to closely-spaced antenna configurations and poor scattering environments, we analyze the exact and lower bound on the symbol error probability (SEP) of the opportunistic DCF relaying over spatially correlated MIMO Rayleigh fading channels. Numerical results show that, even in the presence of spatial fading correlation, the proposed opportunistic relaying scheme is efficient and achieves additional performance gain with low overhead.

The composite binary offset carrier (CBOC) modulated signal contains multi-peaks in its auto-correlation function, which brings ambiguity to the signal acquisition process of a GNSS receiver. Currently, most traditional ambiguity-removing schemes for CBOC signal acquisition approximate CBOC signal as a BOC signal, which may incur performance degradation. Based on Galileo E1 CBOC signal, this paper proposes a novel adaptive ambiguity-removing acquisition scheme which doesn't adopt the approximation used in traditional schemes. According to the energy ratio of each sub-code of CBOC signal, the proposed scheme can self-adjust its local reference code to achieve unambiguous and precise signal synchronization. Monte Carlo simulation is conducted in this paper to analyze the performance of the proposed scheme and three traditional schemes. Simulation results show that the proposed scheme has higher detection probability and less mean acquisition time than the other three schemes, which verify the superiority of the proposed scheme.

The present study aims to investigate the effect of voluntary movements on human temporal perception in multisensory integration. We therefore performed temporal order judgment (TOJ) tasks in audio-tactile integration under three conditions: no movement, involuntary movement, and voluntary movement. It is known that the point of subjective simultaneity (PSS) under the no movement condition, that is, normal TOJ tasks, appears when a tactile stimulus is presented before an auditory stimulus. Our experiment showed that involuntary and voluntary movements shift the PSS to a value that reduces the interval between the presentations of auditory and tactile stimuli. Here, the shift of the PSS under the voluntary movement condition was greater than that under the involuntary movement condition. Remarkably, the PSS under the voluntary movement condition appears when an auditory stimulus slightly precedes a tactile stimulus. In addition, a just noticeable difference (JND) under the voluntary movement condition was smaller than those under the other two conditions. These results reveal that voluntary movements alternate the temporal integration of audio-tactile stimuli. In particular, our results suggest that voluntary movements reverse the temporal perception order of auditory and tactile stimuli and improve the temporal resolution of temporal perception. We discuss the functional mechanism of shifting the PSS under the no movement condition with voluntary movements in audio-tactile integration.

Majority-logic algorithms are devised for decoding non-binary LDPC codes in order to reduce computational complexity. However, compared with conventional belief propagation algorithms, majority-logic algorithms suffer from severe bit error performance degradation. This paper presents a low-complexity reliability-based algorithm aiming at improving error correcting ability of majority-logic algorithms. Reliability measures for check nodes are novelly introduced to realize mutual update between variable message and check message, and hence more efficient reliability propagation can be achieved, similar to belief-propagation algorithm. Simulation results on NB-LDPC codes with different characteristics demonstrate that our algorithm can reduce the bit error ratio by more than one order of magnitude and the coding gain enhancement over ISRB-MLGD can reach 0.2-2.0dB, compared with both the ISRB-MLGD and IISRB-MLGD algorithms. Moreover, simulations on typical LDPC codes show that the computational complexity of the proposed algorithm is closely equivalent to ISRB-MLGD algorithm, and is less than 10% of Min-max algorithm. As a result, the proposed algorithm achieves a more efficient trade-off between decoding computational complexity and error performance.

ID-based authenticated key exchange (ID-AKE) is a cryptographic tool to establish a common session key between parties with authentication based on their IDs. If IDs contain some hierarchical structure such as an e-mail address, hierarchical ID-AKE (HID-AKE) is especially suitable because of scalability. However, most of existing HID-AKE schemes do not satisfy advanced security properties such as forward secrecy, and the only known strongly secure HID-AKE scheme is inefficient. In this paper, we propose a new HID-AKE scheme which achieves both strong security and efficiency. We prove that our scheme is eCK-secure (which ensures maximal-exposure-resilience including forward secrecy) without random oracles, while existing schemes is proved in the random oracle model. Moreover, the number of messages and pairing operations are independent of the hierarchy depth; that is, really scalable and practical for a large-system.

This paper addresses the problems of fingerprint identification and verification when a query fingerprint is taken under conditions that differ from those under which the fingerprint of the same person stored in a database was constructed. This occurs when using a different fingerprint scanner with a different pressure, resulting in a fingerprint impression that is smeared and distorted in accordance with a geometric transformation (e.g., affine or even non-linear). Minutiae points on a query fingerprint are matched and aligned to those on one of the fingerprints in the database, using a set of absolute invariants constructed from the shape and/or size of minutiae triangles depending on the assumed map. Once the best candidate match is declared and the corresponding minutiae points are flagged, the query fingerprint image is warped against the candidate fingerprint image in accordance with the estimated warping map. An identification/verification cost function using a combination of distance map and global directional filterbank (DFB) features is then utilized to verify and identify a query fingerprint against candidate fingerprint(s). Performance of the algorithm yields an area of 0.99967 (perfect classification is a value of 1) under the receiver operating characteristic (ROC) curve based on a database consisting of a total of 1680 fingerprint images captured from 240 fingers. The average probability of error was found to be 0.713%. Our algorithm also yields the smallest false non-match rate (FNMR) for a comparable false match rate (FMR) when compared to the well-known technique of DFB features and triangulation-based matching integrated with modeling non-linear deformation. This work represents an advance in resolving the fingerprint identification problem beyond the state-of-the-art approaches in both performance and robustness.

A queue layout of a graph G consists of a linear order of its vertices, and a partition of its edges into queues, such that no two edges in the same queue are nested. The queuenumber qn(G) is the minimum number of queues required in a queue layout of G. The Cartesian product of two graphs G1 = (V1,E1) and G2 = (V2,E2), denoted by G1 × G2, is the graph with {:v1 ∈ V1 and v2 ∈ V2} as its vertex set and an edge (,) belongs to G1×G2 if and only if either (u1,v1) ∈ E1 and u2 = v2 or (u2,v2) ∈ E2 and u1 = v1. Let Tk1,k2,...,kn denote the n-dimensional toroidal grid defined by the Cartesian product of n cycles with varied lengths, i.e., Tk1,k2,...,kn = Ck1 × Ck2 × … × Ckn, where Cki is a cycle of length ki ≥ 3. If k1 = k2 = … = kn = k, the graph is also called the k-ary n-cube and is denoted by Qnk. In this paper, we deal with queue layouts of toroidal grids and show the following bound: qn(Tk1,k2,...,kn) ≤ 2n-2 if n ≥ 2 and ki ≥ 3 for all i = 1,2,...,n. In particular, for n = 2 and k1,k2 ≥ 3, we acquire qn(Tk1,k2) = 2. Recently, Pai et al. (Inform. Process. Lett. 110 (2009) pp.50-56) showed that qn(Qnk) ≤ 2n-1 if n ≥1 and k ≥9. Thus, our result improves the bound of qn(Qnk) when n ≥2 and k ≥9.

An n-dimensional folded hypercube, denoted by FQn, is an enhanced n-dimensional hypercube with one extra link between nodes that have the furthest Hamming distance. Let FFv (respectively, FFe) denote the set of faulty nodes (respectively, faulty links) in FQn. Under the assumption that every fault-free node in FQn is incident to at least two fault-free links, Hsieh et al. (Inform. Process. Lett. 110 (2009) pp.41-53) showed that if |FFv|+|FFe| ≤ 2n-4 for n ≥ 3, then FQn-FFv-FFe contains a fault-free cycle of length at least 2n-2|FFv|. In this paper, we show that, under the same conditional fault model, FQn with n ≥ 5 can tolerate more faulty elements and provides the same lower bound of the length of a longest fault-free cycle, i.e., FQn-FFv-FFe contains a fault-free cycle of length at least 2n-2|FFv| if |FFv|+|FFe| ≤ 2n-3 for n ≥ 5.

This paper proposes a new approach to defining and expressing algorithms: the notion of task logical algorithms. This notion allows the user to define an algorithm for a task T as a set of agents who can collectively perform T. This notion considerably simplifies the algorithm development process and can be seen as an integration of the sequential pseudocode and logical algorithms. This observation requires some changes to algorithm development process. We propose a two-step approach: the first step is to define an algorithm for a task T via a set of agents that can collectively perform T. The second step is to translate these agents into (higher-order) computability logic.

Pattern-avoiding permutations are permutations where none of the subsequences matches the relative order of a given pattern. Pattern-avoiding permutations are related to practical and abstract mathematical problems and can provide simple representations for such problems. For example, some floorplans, which are used for optimizing very-large-scale integration (VLSI) circuit design, can be encoded into pattern-avoiding permutations. The generation of pattern-avoiding permutations is an important topic in efficient VLSI design and mathematical analysis of patten-avoiding permutations. In this paper, we present an algorithm for generating pattern-avoiding permutations, and extend this algorithm beyond classical patterns to generalized patterns with more restrictions. Our approach is based on the data structure πDDs, which can represent a permutation set compactly and has useful set operations. We demonstrate the efficiency of our algorithm by computational experiments.

In phrase-based statistical machine translation, long distance reordering problem is one of the most challenging issues when translating syntactically distant language pairs. In this paper, we propose a novel reordering model to solve this problem. In our model, reordering is affected by the overall structures of sentences such as listings, reduplications, and modifications as well as the relationships of adjacent phrases. To this end, we reflect global syntactic contexts including the parts that are not yet translated during the decoding process.

In this paper, we show a connection between #P and computing the (real) value of the high order derivative at the origin. Consider, as a problem instance, an integer b and a sufficiently often differentiable function F(x) that is given as a string. Then we consider computing the value F(b)(0) of the b-th derivative of F(x) at the origin. By showing a polynomial as an example, we show that we have FP = #P if we can compute log 2F(b)(0) up to certain precision. The previous statement holds even if F(x) is limited to a function that is analytic at any x ∈ R. It implies the hardness of computing the b-th value of a number sequence from the closed form of its generating function.

A number of well-known learning-based face detectors can achieve extraordinary performance in controlled environments. But face detection under varying illumination is still challenging. Possible solutions to this illumination problem could be creating illumination invariant features or utilizing skin color information. However, the features and skin colors are not sufficiently reliable under difficult lighting conditions. Another possible solution is to do illumination normalization (e.g., Histogram Equalization (HE)) prior to executing face detectors. However, applications of normalization to face detection have not been widely studied in the literature. This paper applies and evaluates various existing normalization methods under the framework of combining the illumination normalization and two learning-based face detectors (Haar-like face detector and LBP face detector). These methods were initially proposed for different purposes (face recognition or image quality enhancement), but some of them significantly improve the original face detectors and lead to better performance than HE according to the results of the comparative experiments on two databases. Meanwhile, we propose a new normalization method called segmentation-based half histogram stretching and truncation (SH) for face detection under varying illumination. It first employs Otsu method to segment the histogram (intensities) of the input image into several spans and then does the redistribution on the segmented spans. In this way, the non-uniform illumination can be efficiently compensated and local facial structures can be appropriately enhanced. Our method obtains good performance according to the experiments.

Homotopy methods are known to be effective methods for finding DC operating points of nonlinear circuits with the theoretical guarantee of global convergence. There are several types of homotopy methods; as one of the most efficient methods for solving bipolar transistor circuits, the variable-gain homotopy (VGH) method is well-known. In this paper, we propose an efficient VGH method for solving bipolar and MOS transistor circuits. We also show that the proposed method converges to a stable operating point with high possibility from any initial point. The proposed method is not only globally convergent but also more efficient than the conventional VGH methods. Moreover, it can easily be implemented in SPICE.

Mobile IPv6 is an IETF (Internet Engineering Task Force) standard which permits node mobility in IPv6. To manage mobility, it establishes a centralized mediator, Home Agent (HA), which inevitably introduces several penalties like triangular routing, single point of failure and limited scalability. Some later extensions such as Global HAHA, which employed multiple HAs, made to alleviate above shortcomings by introducing Distributed Mobility Management (DMM) approach. However, Multiple HA model will not be beneficial, unless the HAs are located finely. But, no major research paper has focused on locating HAs. This paper examines impact of single and multiple HA placements in data plane, by using an Autonomous System (AS) level topology consisting of 30,000 nodes with several evaluation criteria. All possible placements of HA(s) are analysed on a fair, random set of 30,000 node pairs of Mobile Nodes (MN) and Correspondent Nodes (CN). Ultimate result provides a concise account of different HA placements: i.e. cost centrality interprets performance variation better than degree centrality or betweenness. 30,000 ASs are classified into three groups in terms of Freeman's closeness index and betweenness centrality: 1) high range group, 2) mid range group, and 3) low range group. Considering dual HA placement, if one HA is placed in an AS in the high range group, then any subsequent HA placement gives worse results, thus single HA placement is adequate. With the mid range group, similar results are demonstrated by the upper portion of the group, but the rest yields better results when combined with another HA. Finally, from the perspective of low range group, if the subsequent HA is placed in the high range group, it gives better result. On the other hand, betweenness based grouping yields varying results. Consequently, this study reveals that the Freeman's closeness index is most appropriate in determining impacts of HA placements among considered indices.