This paper addresses the attribute recognition problem, a field of research that is dominated by studies in the visible spectrum. Only a few works are available in the thermal spectrum, which is fundamentally different from the visible one. This research performs recognition specifically on wearable attributes, such as glasses and masks. Usually these attributes are relatively small in size when compared with the human body, on top of a large intra-class variation of the human body itself, therefore recognizing them is not an easy task. Our method utilizes a decomposition framework based on Robust Principal Component Analysis (RPCA) to extract the attribute information for recognition. However, because it is difficult to separate the body and the attributes without any prior knowledge, noise is also extracted along with attributes, hampering the recognition capability. We made use of prior knowledge; namely the location where the attribute is likely to be present. The knowledge is referred to as the Probability Map, incorporated as a weight in the decomposition by RPCA. Using the Probability Map, we achieve an attribute-wise decomposition. The results show a significant improvement with this approach compared to the baseline, and the proposed method achieved the highest performance in average with a 0.83 F-score.

Crystalline GaN films can be grown even on amorphous substrates with the use of graphene buffer layers by pulsed sputtering deposition (PSD). The graphene buffer layers allowed us to grow highly c-axis-oriented GaN films at low substrate temperatures. Full-color GaN-based LEDs can be fabricated on the GaN/graphene structures and they are operated successfully. This indicates that the present technique is promising for future large-area light-emitting displays on amorphous substrates.

Thin films of vinyl derivatives of naphthalene diimide were prepared by electron-assisted vapor deposition. Monomer materials of N, N'-bis(allyl)-naphthalene diimide (Allyl-NDI) and N,N'-bis(p-vinyl-benzyl)-naphthalene diimide (Sty-NDI) were newly synthesized for this purpose. Uniform films were obtained by vapor-depositing these materials, whereas spin-coating yielded nonuniform films. IR analysis suggested that Sty-NDI can be polymerized upon vapor deposition. An insoluble film of Sty-NDI was obtained by the electron-assisted vapor deposition. On the other hand, Allyl-NDI had lower reactivity for polymerization. It was concluded that Sty-NDI is a promising material for preparing thin films of vinyl polymer having naphthalene diimide units.

This paper presents the set of procedures to blend GNSS and V2V communication to improve the performance of the stand-alone on-board GNSS receiver and to assure mutual positioning with a bounded error. Particle filter algorithm is applied to enhance mutual positioning of vehicles, and it fuses the information provided by the GNSS receiver, wireless measurements in vehicular environments, odometer, and digital road map data including reachability and zone probabilities. Measurement-based statistical model of relative distance as a function of Time-of-Arrival is experimentally obtained. The number of collaborative vehicles to the mutual positioning procedure is investigated in terms of positioning accuracy and network performance through realistic simulation studies, and the proposed mutual positioning procedure is experimentally evaluated by a fleet of five IEEE 802.11p radio modem equipped vehicles. Collaboration in a VANET improves availability of position measurement and its accuracy up to 40% in comparison with respect to the stand-alone GNSS receiver.

Limited satellite visibility, multipath and non-line-of-sight signals reduce the performance of the stand-alone Global Navigation Satellite System (GNSS) receiver in urban environments. Embedding 3D model of urban structures in the condition of restricted visibility of the GNSS satellites due to urban canyons may improve position measurement accuracy significantly. State-of-the-art methods use raytracing or rasterization techniques applied on a 3D map to detect satellite visibility. But these techniques are computationally expensive and limit their widespread benefits for mobile and automotive applications. In this paper, a texture-based satellite visibility detection (TBSVD) methodology suitable for mobile and automotive grade Graphical Processing Units is presented. This methodology applies ray marching algorithm on a 2D height map texture of urban structures, and it is proposed as a more efficient alternative to 3D raytracing or rasterization methodology. Real road test in the business district of the metropolitan city is conducted in order to evaluate its performance. TBSVD is implemented in conventional ranging-based GNSS solution and the results illustrate the effectiveness of the proposed approach.

In this paper, we explore the relationship between Geometric Dilution of Precision (GDOP) and Cramer-Rao Bound (CRB) by tracing back to the original motivations for deriving these two indexes. In addition, the GDOP is served as a sensor-target geometric uncertainty analysis tool whilst the CRB is served as a statistical performance evaluation tool based on the sensor observations originated from target. And CRB is the inverse matrix of Fisher information matrix (FIM). Based on the original derivations for a same positioning application, we interpret their difference in a mathematical view to show that.

One of major ideas to design a multivariate public key cryptosystem (MPKC) is to generate its quadratic forms by a polynomial map over an extension field. In fact, Matsumoto-Imai's scheme (1988), HFE (Patarin, 1996), MFE (Wang et al., 2006) and multi-HFE (Chen et al., 2008) are constructed in this way and Sflash (Akkar et al., 2003), Quartz (Patarin et al., 2001), Gui (Petzoldt et al, 2015) are variants of these schemes. An advantage of such extension field type MPKCs is to reduce the numbers of variables and equations to be solved in the decryption process. In the present paper, we study the security of MPKCs whose quadratic forms are derived from a “quadratic” map over an extension field and propose a new attack on such MPKCs. Our attack recovers partial information of the secret affine maps in polynomial time when the field is of odd characteristic. Once such partial information is recovered, the attacker can find the plain-text for a given cipher-text by solving a system of quadratic equations over the extension field whose numbers of variables and equations are same to those of the system of quadratic equations used in the decryption process.

This paper deals with the diffraction of a monochromatic plane wave by a periodic grating. We discuss a problem how to obtain a numerical diffraction efficiency (NDE) satisfying the reciprocity theorem for diffraction efficiencies, because diffraction efficiencies are the subject of the diffraction theories. First, this paper introduces a new formula that decomposes an NDE into two components: the even component and the odd one. The former satisfies the reciprocity theorem for diffraction efficiencies, but the latter does not. Therefore, the even component of an NDE becomes an answer to our problem. On the other hand, the odd component of an NDE represents an unwanted error. Using such the decomposition formula, we then obtain another new formula that decomposes the conventional energy error into two components. One is the energy error made by even components of NDE's. The other is the energy error constructed by unwanted odd ones and it may be used as a reciprocity criterion of a numerical solution. This decomposition formula shows a drawback of the conventional energy balance. The total energy error is newly introduced as a more strict condition for a desirable solution. We point out theoretically that the reciprocal wave solution, an approximate solution satisfying the reciprocity for wave fields, gives another solution to our problem. Numerical examples are given for the diffraction of a TM plane wave by a very rough periodic surface with perfect conductivity. In the case of a numerical solution by the image integral equation of the second kind, we found that the energy error is much reduced by use of the even component of an NDE as an approximate diffraction efficiency or by use of a reciprocal wave solution.

The Time Domain Boundary Element Method (TDBEM) has its advantages in the analysis of transient electromagnetic fields (wake fields) induced by a charged particle beam with curved trajectory in a particle accelerator. On the other hand, the TDBEM has disadvantages of huge required memory and computation time compared with those of the Finite Difference Time Domain (FDTD) method or the Finite Integration Technique (FIT). This paper presents a comparison of the FDTD method and 4-D domain decomposition method of the TDBEM based on an initial value problem formulation for the curved trajectory electron beam, and application to a full model simulation of the bunch compressor section of the high-energy particle accelerators.

Object detection is the first step in the object recognition. According to the detection results, its following works are affected. However, object detection has a heavy resource requirement in terms of, computing power and memory. If an image is enlarged, the computational load required for object detection is also increased. An-integral-image-based method guarantees fast object detection. Once an integral image is generated, the speed of the object detection procedure remains fixed, regardless of the pattern region size. However, this becomes an even greater issue if the image is enlarged. In this paper, we propose the use of directional integral image based object detection. A directional integral image gives direction to an integral image, which can then be calculated from various directions. Furthermore, many unnecessary calculations, which typically occur when a partial integral image is used for object detection, can be avoided. Therefore, the amount of computation is reduced, compared with methods using integral images. In experiments comparing methods, the proposed method required 40% fewer computations.

In this paper, we present several cryptanalyses of Hierocrypt-L1 block cipher, which was selected as one of the CRYPTREC recommended ciphers in Japan in 2003. We present a differential attack and an impossible differential attack on 8 S-function layers in a related-key setting. We first show that there exist the key scheduling differential characteristics which always hold, then we search for differential paths for the data randomizing part with the minimum active S-boxes using the above key differentials. We also show that our impossible differential attack is a new type.

Patarin proposed a crytographic trapdoor called Hidden Field Equation (HFE), a trapdoor based on the Multivariate Quadratic (MQ) and the Isomorphism of Polynomials (IP) problems. The MQ problem was proved by Patarin et al.'s to be NP-complete. Although the basic HFE has been proved to be vulnerable to attacks, its variants obtained by some modifications have been proved to be stronger against attacks. The Quartz digital signature scheme based on the HFEv- trapdoor (a variant of HFE) with particular choices of parameters, has been shown to be stronger against algebraic attacks to recover the private key. Furthermore, it generates reasonably short signatures. However, Joux et al. proved (based on the Birthday Paradox Attack) that Quartz is malleable in the sense that, if an adversary gets a valid pair of message and signature, a valid signature to another related message is obtainable with 250 computations and 250 queries to the signing oracle. Currently, the recommended minimum security level is 2112. Our signature scheme is also based on Quartz but we achieve a 2112 security level against Joux et al.'s attack. It is also more efficient in signature verification and vector initializations. Furthermore, we implemented both the original and our improved Quartz signature and run empirical comparisons.

In this paper, we propose a novel decomposition method to segment multiple object regions simultaneously in cluttered videos. This method formulates object regions segmentation as a labeling problem in which we assign object IDs to the superpixels in a sequence of video frames so that the unary color matching cost is low, the assignment induces compact segments, and the superpixel labeling is consistent through time. Multi-object segmentation in a video is a combinatorial problem. We propose a binary linear formulation. Since the integer linear programming is hard to solve directly, we relax it and further decompose the relaxation into a sequence of much simpler max-flow problems. The proposed method is guaranteed to converge in a finite number of steps to the global optimum of the relaxation. It also has a high chance to obtain all integer solution and therefore achieves the global optimum. The rounding of the relaxation result gives an N-approximation solution, where N is the number of objects. Comparing to directly solving the integer program, the novel decomposition method speeds up the computation by orders of magnitude. Our experiments show that the proposed method is robust against object pose variation, occlusion and is more accurate than the competing methods while at the same time maintains the efficiency.

We propose subquadratic space complexity multipliers for any finite field $mathbb{F}_{q^n}$ over the base field $mathbb{F}_q$ using the Dickson basis, where q is a prime power. It is shown that a field multiplication in $mathbb{F}_{q^n}$ based on the Dickson basis results in computations of Toeplitz matrix vector products (TMVPs). Therefore, an efficient computation of a TMVP yields an efficient multiplier. In order to derive efficient $mathbb{F}_{q^n}$ multipliers, we develop computational schemes for a TMVP over $mathbb{F}_{q}$. As a result, the $mathbb{F}_{2^n}$ multipliers, as special cases of the proposed $mathbb{F}_{q^n}$ multipliers, have lower time complexities as well as space complexities compared with existing results. For example, in the case that n is a power of 3, the proposed $mathbb{F}_{2^n}$ multiplier for an irreducible Dickson trinomial has about 14% reduced space complexity and lower time complexity compared with the best known results.

A black mask (BM) is a layer used to improve the display quality by suppressing light leakage. In general, the BM is formed by a photolithography process. In this study, a novel technique for the fabrication of a quasi-black mask (q-BM) is proposed; the q-BM was composed of vertical and hybrid orientation areas, patterned by a separation coating technique using an electro-spray deposition method. Using our technique, the q-BM can be formed easily without the additional masks used for the BM.

The segmentation of Mycobacterium tuberculosis images forms the basis for the computer-aided diagnosis of tuberculosis. The segmented objects are often broken due to the low-contrast objects and the limits of segmentation method. This will result in decreasing the accuracy of segmentation and recognition. A simple and effective post-processing method is proposed to connect the broken objects. The broken objects in the segmented binary images are connected based on the information obtained from their skeletons. Experimental results demonstrate the effectiveness of our proposed method.

We developed flexible LC devices using coat-debond polyimide substrates with a low birefringence and etched post spacers, and clarified that flexible LCDs using post spacers with small spacer distance have a high flexibility without degradation of the image quality. This result ensured the feasibility of flexible LCDs using coat-debond method.

We have proposed composite films composed of a molecular-aligned polymer and liquid crystal (LC) for substrate-free liquid crystal displays with high-contrast images. We successfully controlled the molecular alignment of the LC and formed molecular-aligned LC droplets in the polymer by controlling the fluidity of the LC/monomer mixture and the curing rate of the monomer.

We propose a speech analysis method based on the source-filter model using multivariate empirical mode decomposition (MEMD). The proposed method takes multiple adjacent frames of a speech signal into account by combining their log spectra into multivariate signals. The multivariate signals are then decomposed into intrinsic mode functions (IMFs). The IMFs are divided into two groups using the peak of the autocorrelation function (ACF) of an IMF. The first group characterized by a spectral fine structure is used to estimate the fundamental frequency F0 by using the ACF, whereas the second group characterized by the frequency response of the vocal-tract filter is used to estimate formant frequencies by using a peak picking technique. There are two advantages of using MEMD: (i) the variation in the number of IMFs is eliminated in contrast with single-frame based empirical mode decomposition and (ii) the common information of the adjacent frames aligns in the same order of IMFs because of the common mode alignment property of MEMD. These advantages make the analysis more accurate than with other methods. As opposed to the conventional linear prediction (LP) and cepstrum methods, which rely on the LP order and cut-off frequency, respectively, the proposed method automatically separates the glottal-source and vocal-tract filter. The results showed that the proposed method exhibits the highest accuracy of F0 estimation and correctly estimates the formant frequencies of the vocal-tract filter.

A novel method for illumination-invariant face representation is presented based on the orthogonal decomposition of the local image structure. One important advantage of the proposed method is that image gradients and corresponding intensity values are simultaneously used with our decomposition procedure to preserve the original texture while yielding the illumination-invariant feature space. Experimental results demonstrate that the proposed method is effective for face recognition and verification even with diverse lighting conditions.