Most previous approaches on comparing the results for software architecture recovery are designed to handle only flat decompositions. In this paper, we propose a novel distance called Split-Jaccard Distance of Hierarchical Decompositions. It extends the Jaccard coefficient and incorporates the concept of the splits of leaves in a hierarchical decomposition. We analyze the proposed distance and derive its properties, including the lower-bound and the metric space.

This paper presents a filtering method for efficient face image retrieval over large volume of face databases. The proposed method employs a new face image descriptor, called a cell-orientation vector (COV). It has a simple form: a 72-dimensional vector of integers from 0 to 8. Despite of its simplicity, it achieves high accuracy and efficiency. Our experimental results show that the proposed method based on COVs provides better performance than a recent approach based on identity-based quantization in terms of both accuracy and efficiency.

The indoor fingerprinting localization technology has received more attention in recent years due to the increasing demand of the indoor location based services (LBSs). However, a high quality of the LBS requires a positioning solution with high accuracy and low computational complexity. The particle swarm optimization (PSO) technique, which emulates the social behavior of a flock of birds to search for the optimal solution of a special problem, can provide attractive performance in terms of accuracy, computational efficiency and convergence rate. In this paper, we adopt the PSO algorithm to estimate the location information. First, our system establishes a Bayesian-rule based objective function. It then applies PSO to identify the optimal solution. We also propose a hybrid access point (AP) selection method to improve the accuracy, and analyze the effects of the number and the initial positions of particles on the localization performance. In order to mitigate the estimation error, we use the Kalman Filter to update the initial estimated location via the PSO algorithm to track the trail of the mobile user. Our analysis indicates that our method can reduce the computational complexity and improve the real-time performance. Numerous experiments also demonstrate that our proposed localization and tracking system achieve higher localization accuracy than existing systems.

Recently, Gan and Luo have proposed a direction-of-arrival estimation method for uncorrelated and coherent signals in the presence of multipath propagation [3]. In their method, uncorrelated and coherent signals are distinguished by rotational invariance techniques and the property of the moduli of eigenvalues. However, due to the limitation of finite number of sensors, the pseudo-inverse matrix derived in this method is an approximate one. When the number of sensors is small, the approximation error is large, which adversely affects the property of the moduli of eigenvalues. Consequently, the method in [3] performs poorly in identifying uncorrelated signals under such circumstance. Moreover, in cases of small number of snapshots and low signal to noise ratio, the performance of their method is poor as well. Therefore, in this letter we first study the approximation in [3] and then propose an improved method that performs better in distinguishing between uncorrelated signals and coherent signals and in the aforementioned two cases. The simulation results demonstrate the effectiveness and efficiency of the proposed method.

In automotive frequency modulated continuous wave (FMCW) radar based on multiple ramps with different slope, an effective pairing algorithm is required to simultaneously detect the target range and velocity. That is, as finding beat-frequencies intersecting at a single point of the range-Doppler map, we extract the range and velocity of a target. Unlike the ideal case, however, in a real radar system, even though multiple beat frequencies are originated from the same target, these beat frequencies have many different intersection values, resulting in mismatch pairing during the pairing step. Moreover, this problem also reduces the detection accuracy and the radar detection performance. In this study, we found that mismatch pairing is caused by the round-off errors of the range-beat frequency and Doppler frequency, as well as their various combinations in the discrete frequency domain. We also investigated the effect of mismatch pairing on detection performance, and proposed a new approach to minimize this problem. First, we propose integer and half-integer frequency position-based pairing method during extraction of the range and Doppler frequencies in each ramp to increase detection accuracy. Second, we propose a window-based pairing method to identify the same target from range-Doppler frequencies extracted in the first step. We also find the appropriate window size to overcome pairing mismatch. Finally, we propose the method to obtain a higher accuracy of range and velocity by weighting the values determined in one window. To verify the detection performance of the proposed method by comparison with the typical method, simulations were conducted. Then, in a real field test using the developed radar prototype, the detection probability of the proposed algorithm showed more than 60% improvement in comparison with the conventional method.

We present an algorithm for efficient rendering of animated hair under a dynamic, low-frequency lighting environment. We use spherical harmonics (SH) to represent the environmental light. The transmittances between a point on a hair strand and the light sources are also represented by SH functions. Then, a convolution of SH functions and the scattering function of a hair strand is precomputed. This allows us to efficiently compute the intensity at a point on the hair. However, the computation of the transmittance is very time-consuming. We address this problem by using a voxel-based approach: the transmittance is computed by using a voxelized hair model. We further accelerate the computation by sampling the voxels. By using our method, we can render a hair model consisting of tens of thousands of hair strands at interactive frame rates.

A secret sharing scheme is said to be d-multiplicative if the scheme allows the players to multiply shared d secrets by locally converting their shares into an additive sharing of the product. In the previous work, the following negative result for perfect secret sharing has been shown: The d-multiplicative secret sharing for d players is impossible. This paper extends the impossibility result to non-perfect secret sharing. Our main result is a proof that d-multiplicative secret sharing for d players is impossible even if every player has partial information on the secret (e.g., all but one bit). This result means that there is no need to relax the privacy requirement with leakage of partial information only for the purpose of d-multiplication.

We report a real time method to monitor the chemical reaction in microdroplets, which contain an organic dye, 5(6)-carboxynaphthofluorescein and a CdSe/ZnS quantum dot using fluorescence spectra. Especially, the relationship between the droplet size and the reaction rate of the two reagents was investigated by changing an injection speed.

We demonstrated a novel technique to fabricate nanosized structures on a Nafion membrane, using thermal nanoimprinting with alinebreak $5 imes 5$,$mu $m$^{mathrm{2}}$ square pattern Si mold without any polymer damage. A 24,MPa thermal imprinting pressure was used for 10,min. We observed high aspect ratio ($sim$1:10) pillars on the surface after imprinting at 200$^{circ}$C. Finally, we used a novel quartz mold with a 200,nm resolution dot pattern.

In this paper, we present a new algorithm for fast online motion segmentation with low time complexity. Feature points in each input frame of an image stream are represented as a spatial neighbor graph. Then, the affinities for each point pair on the graph, as edge weights, are computed through our effective motion analysis based on multi-temporal intervals. Finally, these points are optimally segmented by agglomerative hierarchical clustering combined with normalized modularity maximization. Through experiments on publicly available datasets, we show that the proposed method operates in real time with almost linear time complexity, producing segmentation results comparable with those of recent state-of-the-art methods.

In several important applications, we often encounter with the computation of a Toeplitz matrix vector product (TMVP). In this work, we propose a k-way splitting method for a TMVP over any field F, which is a generalization of that over GF(2) presented by Hasan and Negre. Furthermore, as an application of the TMVP method over F, we present the first subquadratic space complexity multiplier over any finite field GF(pn) defined by an irreducible trinomial.

Secret sharing scheme (SS) has been extensively studied since SSs are important not only for secure data storage but also as a fundamental building block for multiparty computation (MPC). For an application to secure data storage, the share size of SS is an important factor. For an application to a building block for MPC, the extendibility to MPC is needed. Computationally secure SSs and a ramp scheme have a small share size but there have been few studies concerning their MPC. In contrast, there have been many studies about MPC on Shamir's and replicated SSs while their share size is large. We consider an application scenario of SS such as applying SSs to secure data storage service with MPC. In this application, users store their data in servers through SS, and sometimes the servers perform MPC as an optional feature. In this case, the extendibility to MPC is needed and good code-efficiency is preferable. We propose a new computational SS, and show how to convert shares of our SS and a ramp SS to those of multiparty-friendly SS such as Shamir's and replicated SS. This enables one to secretly-share data compactly and extend secretly-shared data to MPC if needed.

Feedback with carry shift registers (FCSRs) implemented using Galois representation have been found to have a weakness called LFSRization. It leads to powerful attacks against the stream ciphers based on them. A new representation called ring representation has been proposed to avoid the attacks. It was considered to circumvent the weaknesses of Galois FCSRs. This correspondence presents a class of ring FCSRs, which meet the implementation criteria, but are still possible to maintain linear behavior for several clock cycles. Their LFSRization probability and how to improve their security are also mentioned.

Rainbow is one of signature schemes based on the problem solving a set of multivariate quadratic equations. While its signature generation and verification are fast and the security is presently sufficient under suitable parameter selections, the key size is relatively large. Recently, Quaternion Rainbow — Rainbow over a quaternion ring — was proposed by Yasuda, Sakurai and Takagi (CT-RSA'12) to reduce the key size of Rainbow without impairing the security. However, a new vulnerability emerges from the structure of quaternion ring; in fact, Thomae (SCN'12) found that Quaternion Rainbow is less secure than the same-size original Rainbow. In the present paper, we further study the structure of Quaternion Rainbow and show that Quaternion Rainbow is one of sparse versions of the Rainbow. Its sparse structure causes a vulnerability of Quaternion Rainbow. Especially, we find that Quaternion Rainbow over even characteristic field, whose security level is estimated as about the original Rainbow of at most 3/4 by Thomae's analysis, is almost as secure as the original Rainbow of at most 1/4-size.

We propose a novel phased array-fed dual-reflector antenna that reduces performance degradation caused by multiple reflection. The marked feature of the proposed configuration is that different reflector profiles are employed for the two orthogonal directions. The reflector profile in the beam-scanning section (vertical section) is set to an imaging reflector configuration, while the profile in the orthogonal non-beam-scanning section (horizontal section) is set to a ring-focus Cassegrain antenna configuration. In order to compare the proposed antenna with the conventional antenna in which multiple reflection was problematic, we designed a prototype antenna of the same size, and verified the validity of the proposed antenna. The results of the verification were that the gain in the designed central frequency increased by 0.4 dB, and the ripple of the gain frequency properties that was produced by multiple reflection was decreased by 1.1,dB. These results demonstrated the validity of the proposed antenna.

Primitive linear recurring sequences over rings are important in modern communication technology, and character sums of such sequences are used to analyze their statistical properties. We obtain a new upper bound for the character sum of primitive sequences of order n over the residue ring modulo a square-free odd integer m, and thereby improve previously known bound mn/2.

Secret sharing (SS) has been extensively studied as for both secure data storage and a fundamental building block for multiparty computation (MPC). Recently, Kikuchi et al. proposed a passively and unconditionally secure conversion protocol that converts from a share of a ramp scheme to another of homomorphic SS scheme. The share-size of the ramp scheme is small, and the homomorphic SS scheme is a class of SS schemes that includes Shamir's and replicated SS schemes, which are convenient for MPC. Therefore, their protocol is a conversion from an SS scheme whose share-size is small to MPC-friendly SS schemes, and can be applied to reduce the amount of data storage while maintaining extendibility to MPC. We propose five unconditionally and actively secure protocols in the honest majority. In this paper, we consider a privacy and correctness as security requirement and does not consider a robustness: A cheat caused by an active adversary must be detected. These protocols consist of two conversion protocols, two reveal protocols and a protocol generating specific randomness. Main protocols among them are two conversion protocols for bilateral conversion between a ramp scheme and linear SS scheme, and the others are building blocks of the main protocols. Linear SS scheme is a subset of homomorphic SS scheme but includes both Shamir's and replicated SS schemes. Therefore, these main protocols are conversions between an SS scheme whose share-size is small to MPC-friendly SS schemes. These main protocols are unconditionally and actively secure so if MPC protocols used after the conversion are actively secure, the whole system involving SS scheme, conversion, and MPC protocols can be unconditionally and actively secure by using our main protocols. One of our two main protocols is the first to convert from MPC-friendly SS schemes to the ramp scheme. This enhances applications, such as secure backup, of the conversion protocol. Other than the two main protocols, we propose a protocol for generating specific randomnesses and two reveal protocols as building blocks. The latter two reveal protocols are actively and unconditionally secure in the honest majority and requires O(n||F||)-bit communication per revealing, and we believe that it is independently interest.

The concept of dual pairing vector spaces (DPVS) was introduced by Okamoto and Takashima in 2009, and it has been employed in various applications, functional encryption (FE) including attribute-based encryption (ABE) and inner-product encryption (IPE) as well as attribute-based signatures (ABS), generic conversion from composite-order group based schemes to prime-order group based ones and public-key watermarking. In this paper, we show the concept of DPVS, the major applications to FE and the key techniques employed in these applications. This paper presents them with placing more emphasis on plain and intuitive descriptions than formal preciseness.

While online social networking is a popular way for people to share information, it carries the risk of unintentionally disclosing personal information. One way to reduce this risk is to anonymize personal information in messages before they are posted. Furthermore, if personal information is somehow disclosed, the person who disclosed it should be identifiable. Several methods developed for anonymizing personal information in natural language text simply remove sensitive phrases, making the anonymized text message unnatural. Other methods change the message by using synonymization or structural alteration to create fingerprints for detecting disclosure, but they do not support the creation of a sufficient number of fingerprints for friends of an online social network user. We have developed a system for anonymizing personal information in text messages that generalizes sensitive phrases. It also creates a sufficient number of fingerprints of a message by using synonyms so that, if personal information is revealed online, the person who revealed it can be identified. A distribution metric is used to ensure that the degree of anonymization is appropriate for each group of friends. A threshold is used to improve the naturalness of the fingerprinted messages so that they do not catch the attention of attackers. Evaluation using about 55,000 personal tweets in English demonstrated that our system creates sufficiently natural fingerprinted messages for friends and groups of friends. The practicality of the system was demonstrated by creating a web application for controlling messages posted on Facebook.

A threshold secret sharing scheme protects content by dividing it into many pieces and distributing them among different servers. This scheme can also be utilized for the reliable delivery of important content. Thanks to this scheme, the receiver can still reconstruct the original content even if several pieces are lost during delivery due to a multiple-link failure. Nevertheless, the receiver cannot reconstruct the original content unless it receives pieces more than or equal to the threshold. This paper aims to obtain reliable delivery routes for the pieces, as this will minimize the probability that the receiver cannot reconstruct the original content. Although such a route optimization problem can be formulated using an integer linear programming (ILP) model, computation of globally optimum delivery routes based on the ILP model requires large amounts of computational resources. Thus, this paper proposes a lightweight method for computing suboptimum delivery routes. The proposed greedy method computes each of the delivery routes successively by using the conventional shortest route algorithm repeatedly. The link distances are adjusted iteratively on the basis of the given probability of failure on each link and they are utilized for the calculation of each shortest route. The results of a performance evaluation show that the proposed method can compute sub-optimum delivery routes efficiently thanks to the precise adjustment of the link distances, even in backbone networks on a real-world scale.