One of the major challenges facing the design of a routing protocol for Wireless Sensor Networks (WSNs) is to find the most reliable path between the source and sink node. Furthermore, a routing protocol for WSN should be well aware of sensor limitations. In this paper, we present an energy efficient, scalable, and distributed node disjoint multipath routing algorithm. The proposed algorithm, the Energy-aware Multipath Routing Algorithm (EMRA), adjusts traffic flows via a novel load balancing scheme. EMRA has a higher average node energy efficiency, lower control overhead, and a shorter average delay than those of well-known previous works. Moreover, since EMRA takes into consideration network reliability, it is useful for delivering data in unreliable environments.

In this paper, we proposed a new high-rate oblique deposition method using two sputtering sources to obtain SiO2 films for a liquid crystal alignment layer. One sputtering source that operates in a metal mode supplies Si atoms to a substrate, and the other source that operates in an oxide mode supplies oxygen radicals to a substrate. To reduce the gas pressure of a deposition chamber and make the two sputtering sources operate in different modes, the sputtering sources were separated from the deposition chamber with stainless meshes, and Ar and oxygen gases were introduced separately through the two sputtering sources, i.e., Ar gas was introduced through the Si supply source and oxygen gas was introduced through the oxygen radical source. When Ar gas of 30 sccm and oxygen gas of 4 sccm were introduced into the system, the gas pressure of the deposition chamber was maintained below 1.7 mTorr and the films deposited at an incidence angle of more than 70 showed an elongated inclined columnar structure. Under this condition, a deposition rate of 30 nm/min was realized even at an incidence angle above 70, where most of the Si atoms incident to the substrate were supplied by the Si supply source and the oxygen radical source supplied oxygen radicals and promoted the oxidation of the film.

For RSA, May showed a deterministic polynomial time equivalence of computing d to factoring N(=pq). On the other hand, Takagi showed a variant of RSA such that the decryption algorithm is faster than the standard RSA, where N=prq while ed=1 mod(p-1)(q-1). In this paper, we show that a deterministic polynomial time equivalence also holds in this variant. The coefficient matrix T to which LLL algorithm is applied is no longer lower triangular, and hence we develop a new technique to overcome this problem.

For AES 128 security level there are several natural choices for pairing-friendly elliptic curves. In particular, as we will explain, one might choose curves with k=9 or curves with k=12. The case k=9 has not been studied in the literature, and so it is not clear how efficiently pairings can be computed in that case. In this paper, we present efficient methods for the k=9 case, including generation of elliptic curves with the shorter Miller loop, the denominator elimination and speed up of the final exponentiation. Then we compare the performance of these choices. From the analysis, we conclude that for pairing-based cryptography at the AES 128 security level, the Barreto-Naehrig curves are the most efficient choice, and the performance of the case k=9 is comparable to the Barreto-Naehrig curves.

In this paper, two new clustering algorithms based on fuzzy c-means for data with tolerance using kernel functions are proposed. Kernel functions which map the data from the original space into higher dimensional feature space are introduced into the proposed algorithms. Nonlinear boundary of clusters can be easily found by using the kernel functions. First, two clustering algorithms for data with tolerance are introduced. One is based on standard method and the other is on entropy-based one. Second, the tolerance in feature space is discussed taking account into soft margin algorithm in Support Vector Machine. Third, two objective functions in feature space are shown corresponding to two methods, respectively. Fourth, Karush-Kuhn-Tucker conditions of two objective functions are considered, respectively, and these conditions are re-expressed with kernel functions as the representation of an inner product for mapping from the original pattern space into a higher dimensional feature space. Fifth, two iterative algorithms are proposed for the objective functions, respectively. Through some numerical experiments, the proposed algorithms are discussed.

The steady approach of advanced nations toward realization of ubiquitous computing societies has given birth to rapidly growing demands for new-generation distributed computing (DC) applications. Consequently, economic and reliable construction of new-generation DC applications is currently a major issue faced by the software technology research community. What is needed is a new-generation DC software engineering technology which is at least multiple times more effective in constructing new-generation DC applications than the currently practiced technologies are. In particular, this author believes that a new-generation building-block (BB), which is much more advanced than the current-generation DC object that is a small extension of the object model embedded in languages C++, Java, and C#, is needed. Such a BB should enable systematic and economic construction of DC applications that are capable of taking critical actions with 100-microsecond-level or even 10-microsecond-level timing accuracy, fault tolerance, and security enforcement while being easily expandable and taking advantage of all sorts of network connectivity. Some directions considered worth pursuing for finding such BBs are discussed.

The ηT pairing for supersingular elliptic curves over GF(3m) has been paid attention because of its computational efficiency. Since most computation parts of the ηT pairing are GF(3m) multiplications, it is important to improve the speed of the multiplication when implementing the ηT pairing. In this paper we investigate software implementation of GF(3m) multiplication and propose using irreducible trinomials xm+axk+b over GF(3) such that k is a multiple of w, where w is the bit length of the word of targeted CPU. We call the trinomials "reduction optimal trinomials (ROTs)." ROTs actually exist for several m's and for typical values of w = 16 and 32. We list them for extension degrees m = 97, 167, 193, 239, 317, and 487. These m's are derived from security considerations. Using ROTs, we are able to implement efficient modulo operations (reductions) for GF(3m) multiplication compared with cases in which other types of irreducible trinomials are used (e.g., trinomials with a minimum k for each m). The reason for this is that for cases using ROTs, the number of shift operations on multiple precision data is reduced to less than half compared with cases using other trinomials. Our implementation results show that programs of reduction specialized for ROTs are 20-30% faster on 32-bit CPU and approximately 40% faster on 16-bit CPU compared with programs using irreducible trinomials with general k.

In this paper, a motion evaluation technique for rehabilitation training is introduced. Motion recognition technologies have been developed for determining matching motions in the training set. However, we need to measure how well and how much of the motion has been followed for training motion evaluation. We employed a Finite State Machine as a framework of motion evaluation. For similarity analysis, we used weighted angular value differences although any template matching algorithm may be used. For robustness under illumination changes, IR LED's and cameras with IR-pass filter were used. Developed technique was successfully used for rehabilitation training of the disabled. Therapists appraised the system as practically useful.

Clustering is indispensable to obtain a general view of series data from a number of data such as gene expression profiles. We propose a novel metric for clustering. The proposed metric automatically normalizes data to minimize a logarithmic scale distance between the data series.

Spectral subtraction is commonly used for speech enhancement in a single channel system because of the simplicity of its implementation. However, this algorithm introduces perceptually musical noise while suppressing the background noise. We propose a wavelet-based approach in this paper for suppressing the background noise for speech enhancement in a single channel system. The wavelet packet transform, which emulates the human auditory system, is used to decompose the noisy signal into critical bands. Wavelet thresholding is then temporally adjusted with the noise power by time-adapted noise estimation. The proposed algorithm can efficiently suppress the noise while reducing speech distortion. Experimental results, including several objective measurements, show that the proposed wavelet-based algorithm outperforms spectral subtraction and other wavelet-based denoising approaches for speech enhancement for nonstationary noise environments.

The Hajos calculus is a nondeterministic procedure which generates the class of non-3-colorable graphs. If all non-3-colorable graphs can be constructed in polynomial steps by the calculus, then NP = co-NP holds. Up to date, however, it remains open whether there exists a family of graphs that cannot be generated in polynomial steps. To attack this problem, we propose two graph calculi PHC and PHC* that generate non-3-colorable planar graphs, where intermediate graphs in the calculi are also restricted to be planar. Then we prove that PHC and PHC* are sound and complete. We also show that PHC* can polynomially simulate PHC.

In Shamir's (k,n)-threshold secret sharing scheme (threshold scheme)[1], a heavy computational cost is required to make n shares and recover the secret from k shares. As a solution to this problem, several fast threshold schemes have been proposed. However, there is no fast ideal (k,n)-threshold scheme, where k and n are arbitrary. This paper proposes a new fast (k,n)-threshold scheme which uses just EXCLUSIVE-OR(XOR) operations to make n shares and recover the secret from k shares. We prove that every combination of k or more participants can recover the secret, but every group of less than k participants cannot obtain any information about the secret in the proposed scheme. Moreover, the proposed scheme is an ideal secret sharing scheme similar to Shamir's scheme, in which every bit-size of shares equals that of the secret. We also evaluate the efficiency of the scheme, and show that our scheme realizes operations that are much faster than Shamir's.

Wireless sensor network (WSN) is a promising approach for a variety of applications. Routing protocol for WSNs is very challenging because it should be simple, scalable, energy-efficient, and robust to deal with a very large number of nodes, and also self-configurable to node failures and changes of the network topology dynamically. Recently, many researchers have focused on developing hierarchical protocols for WSNs. However, most protocols in the literatures cannot scale well to large sensor networks and difficult to apply in the real applications. In this paper, we propose a novel adaptive routing protocol for WSNs called ARPEES. The main design features of the proposed method are: energy efficiency, dynamic event clustering, and multi-hop relay considering the trade-off relationship between the residual energy available of relay nodes and distance from the relay node to the base station. With a distributed and light overhead traffic approach, we spread energy consumption required for aggregating data and relaying them to different sensor nodes to prolong the lifetime of the whole network. In this method, we consider energy and distance as the parameters in the proposed function to select relay nodes and finally select the optimal path among cluster heads, relay nodes and the base station. The simulation results show that our routing protocol achieves better performance than other previous routing protocols.

Constructing ideal (t,n) threshold secret sharing schemes leads to some limitations on the maximum number of users, that are able to join the secret sharing scheme. We aim to remove these limitations by reducing the information rate of the constructed threshold secret sharing schemes. In this paper we propose recursive construction algorithms of (t,n) threshold secret sharing schemes, based on the generalized vector space construction. Using these algorithms we are able to construct a (t,n) threshold secret sharing scheme for any arbitrary n.

In this letter, we propose a simple detection ordering which can be applied to successive interference cancellation in low-complexity equalization of OFDM in doubly selective channels. Since the detection ordering can be determined solely on the basis of pilot symbol arrangement, the proposed scheme can lead to a significant performance improvement without additional complexity on the premise that pilot symbols are employed primarily for channel estimation.

This paper presents a closed form solution to a problem of constructing the best lower bound of a convex function under certain conditions. The function is assumed (I) bounded below by -ρ, and (II) differentiable and its derivative is Lipschitz continuous with Lipschitz constant L. To construct the lower bound, it is also assumed that we can use the values ρ and L together with the values of the function and its derivative at one specified point. By using the proposed lower bound, we derive a computationally efficient deep monotone approximation operator to the level set of the function. This operator realizes better approximation than subgradient projection which has been utilized, as a monotone approximation operator to level sets of differentiable convex functions as well as nonsmooth convex functions. Therefore, by using the proposed operator, we can improve many signal processing algorithms essentially based on the subgradient projection.

A binaural hearing assistance system based on the frequency domain binaural model has been previously proposed. The system can enhance a signal coming from a specific direction. Since the system utilizes a binaural signal, an inter-channel communication between left and right subsystems is required. The bit rate reduction in inter-channel communication is essential for the detachment of the headset from the processing system. In this paper, the performance of a system which uses a differential pulse code modulation codec is examined and the relationship between the bit rate and sound quality is discussed.

Wireless Sensor Networks (WSNs) have become a key technology for ubiquitous computing environments. In WSNs, battery recharge or replacement is impossible because sensors are left unattended after deployment. Therefore, WSNs need a networking protocol scheme to increase the life time of sensor nodes. The clustering technique is an efficient approach for reducing energy consumption in wireless sensor networks. In cluster topology, however, there is a problem which causes a large amount of energy consumption of cluster head. In addition, in the sparsely deployed sensor field, mesh topology can be more energy-efficient than cluster topology. In this paper, we propose a Hybrid Cluster Mesh (HCM) scheme, which recognizes the density of neighbor nodes and each node decides its topology itself, and HCM-RO (reorganization) scheme which reorganizes clusters. Simulation results show that the proposed hybrid topology control scheme is more energy-efficient than each topology of cluster or mesh.

In this letter, a new estimation filtering is proposed when a delay between signal generation and signal estimation exists. The estimation filter is developed under a maximum likelihood criterion using only the finite observations on the delay interval. The proposed estimation filter is represented in both matrix form and iterative form. It is shown that the filtered estimate has good inherent properties such as time-invariance, unbiasedness and deadbeat. Via numerical simulations, the performance of the proposed estimation filtering is evaluated by the comparison with that of the existing fixed-lag smoothing, which shows that the proposed approach could be appropriate for fast estimation of signals that vary relatively quickly. Moreover, the on-line computational complexity of the proposed estimation filter is shown to be maintained at a lower level than the existing one.

Recently, for more efficient filtering of XML data, YFilter system has been suggested to exploit the prefix commonalities that exist among path expressions. Sharing the prefix commonality gives the benefit of improving filtering performance through the tremendous reduction in filtering machine size. However, exploiting the postfix commonality can also be useful for an XML filtering situation. For example, when a stream of XML messages does not have any defined schema, or users cannot remember the defined schema exactly, users often use the partial matching path queries which begins with the descendant axis ("//"), e.g., '//science/article/title', '//entertainment/article/title', and '//title'. If so, the registered XPath queries are most likely to have the postfix commonality, e.g., the sample queries share the partial path expressions 'article/title' and 'title'. Therefore, in this paper, we introduce a bottom-up filtering approach exploiting the postfix commonality against the top-down approach of YFilter exploiting the prefix commonality. Some experimental results show that our method has better filtering performance when registered XPath queries mainly consist of the partial matching path queries with the postfix commonality.