We investigated oxidation time dependence of graphene oxide employing modified Hummer method by dynamic light scattering. Oxidation reaction proceeded rapidly within about 24 hours, and was saturated. It is suggested that graphene oxides were not able to freely fragment. This implies that the oxidation reactions occur at the limited sites.

Fluoropolymer thin films were prepared by the ion-assisted vapor deposition polymerization (IAD) of 2-(perfluorohexyl)ethylacrylate (Rf-6). The adhesion strength of the film to substrates was estimated by sonicating the films in water and by immersing the films into dichloro-pentafluoro propane (HCFC225). The Rf-6 polymer films by IAD showed stronger adhesion to glass compared to a spin-coated Teflon AF film. The adhesion strength was improved with increasing ion energy Eion of IAD. The IAD films showed superior adhesion to PET surface compared to the glass substrate. The Rf-6 polymer film was effective as a single-layer antireflective coating. The refractive index of the film was 1.368 (λ = 546 nm), which increased slightly with increasing Eion. IAD can be a promising method to prepare fluoropolymer thin films due to the solvent-less process and the flexibility in controlling the film characteristics by the ion energy.

An automotive operating system is a typical safety-critical software and therefore requires extensive analysis w.r.t its effect on system safety. Our earlier work [1] reported a systematic model checking approach for checking the safety properties of the OSEK/VDX-based operating system Trampoline. This article reports further performance improvement using embeddedC constructs for efficient verification of the Trampoline model developed in the earlier work. Experiments show that the use of embeddedC constructs greatly reduces verification costs.

The objective of our research is to build a statistical test that can evaluate different risks of a portfolio selection model with fuzzy data. The central points and radiuses of fuzzy numbers are used to determine the portfolio selection model, and we statistically evaluate the best return by a fuzzy statistical test. Empirical studies are presented to illustrate the risk evaluation of the portfolio selection model with interval values. We conclude that the fuzzy statistical test enables us to evaluate a stable expected return and low risk investment with different choices for k, which indicates the risk level. The results of numerical examples show that our method is suitable for short-term investments.

Enocoro-128v2 is a lightweight stream cipher submitted to Cryptography Research and Evaluation Committees (CRYPTREC). In this paper, we first describe a side channel attack on Enocoro-128v2. We show that all secret key bytes of Enocoro-128v2 can be recovered by correlation power analysis, and it is shown by an experiment that around 6000 traces are needed to recover the secret key on SASEBO-GII (Side-channel Attack Standard Evaluation Board). We second propose a countermeasure with threshold implementation technique, which allows Enocoro-128v2 to be resistant against correlation power analysis as long as less than 105 traces are used.

A novel shadow removal approach is proposed by using block-wise transform domain shadow detection. The approach is based on the fact that the spatial frequency distributions on normal background areas and those under casted shadows from foreground objects are the same. The proposed approach is especially useful for silhouette extraction by using the Gaussian Mixture background Model (GMM) foreground segmentation in the transform domain, because the frequency distribution has already been calculated in the foreground segmentation. The stable shadow removal is realized, due to the transform domain implementation.

It has been reported that the temporal change of current during the deposition shows a plateau and a break, similar to those found in a photocurrent profile taken by the time-of-flight technique for the investigation of photocarrier dynamics in condensed matters, enabling the estimation of electrophoretic mobility of colloidal particles in the suspension. The estimation of the electrophoretic mobility from transient current during the deposition by the simple drift model is based on the assumption that a constant electric field is uniformly applied between the positive and negative electrodes. Therefore, it is important to check if this assumption is satisfied. It is also important to measure the temporal evolution of film thickness, because this may give information about uniformity of colloidal size in the suspension. This study addresses these topics and validity of the assumption is confirmed.

Observing the security of existing identity-based proxy signature schemes was proven in the random oracle model, Cao et al. proposed the first direct construction of identity-based proxy signature secure in the standard model by making use of the identity-based signature due to Paterson and Schuldt. They also provided a security proof to show their construction is secure against forgery attacks without resorting to the random oracles. Unfortunately, in this letter, we demonstrate that their scheme is vulnerable to insider attacks. Specifically, after a private-key extraction query, an adversary, behaving as a malicious original signer or a malicious proxy signer, is able to violate the unforgeability of the scheme.

In this paper, a symbol-rate clock recovery scheme for a receiver that uses an integrating decision feedback equalizer (DFE) is proposed. The proposed clock recovery using expected received signal amplitudes as the criterion realizes minimum mean square error (MMSE) clock recovery. A receiver architecture using an integrating DFE with the proposed symbol-rate clock recovery is also proposed. The proposed clock recovery algorithm successfully recovered the clock phase in a system level simulation only with a DFE. Higher jitter tolerance than 0.26 UIPP at 10 Gb/s operation was also confirmed in the simulation with an 11 dB channel loss at 5 GHz.

This survey provides a brief introduction to compressed sensing as well as several major algorithms to solve it and its various applications to communications systems. We firstly review linear simultaneous equations as ill-posed inverse problems, since the idea of compressed sensing could be best understood in the context of the linear equations. Then, we consider the problem of compressed sensing as an underdetermined linear system with a prior information that the true solution is sparse, and explain the sparse signal recovery based on 1 optimization, which plays the central role in compressed sensing, with some intuitive explanations on the optimization problem. Moreover, we introduce some important properties of the sensing matrix in order to establish the guarantee of the exact recovery of sparse signals from the underdetermined system. After summarizing several major algorithms to obtain a sparse solution focusing on the 1 optimization and the greedy approaches, we introduce applications of compressed sensing to communications systems, such as wireless channel estimation, wireless sensor network, network tomography, cognitive radio, array signal processing, multiple access scheme, and networked control.

This paper presents an approach for cross-pose face recognition by virtual view generation using an appearance clustering based local view transition model. Previously, the traditional global pattern based view transition model (VTM) method was extended to its local version called LVTM, which learns the linear transformation of pixel values between frontal and non-frontal image pairs from training images using partial image in a small region for each location, instead of transforming the entire image pattern. In this paper, we show that the accuracy of the appearance transition model and the recognition rate can be further improved by better exploiting the inherent linear relationship between frontal-nonfrontal face image patch pairs. This is achieved based on the observation that variations in appearance caused by pose are closely related to the corresponding 3D structure and intuitively frontal-nonfrontal patch pairs from more similar local 3D face structures should have a stronger linear relationship. Thus for each specific location, instead of learning a common transformation as in the LVTM, the corresponding local patches are first clustered based on an appearance similarity distance metric and then the transition models are learned separately for each cluster. In the testing stage, each local patch for the input non-frontal probe image is transformed using the learned local view transition model corresponding to the most visually similar cluster. The experimental results on a real-world face dataset demonstrated the superiority of the proposed method in terms of recognition rate.

Let Gs=(Vs, Es) be a simple connected graph. A vertex v ∈ Vs is an articulation vertex if deletion of v and its incident edges from Gs disconnects the graph into at least two connected components. Finding all articulation vertices of a given graph is called the articulation vertex problem. A vertex u ∈ Vs is called a hinge vertex if there exist any two vertices x and y in Gs whose distance increase when u is removed. Finding all hinge vertices of a given graph is called the hinge vertex problem. These problems can be applied to improve the stability and robustness of communication network systems. In this paper, we propose linear time algorithms for the articulation vertex problem and the hinge vertex problem of circular permutation graphs.

We report enhanced photocurrent properties of dye/Au-loaded titanium dioxide (TiO2) films on Au gratings. Au-loaded TiO2 nanopowders were first synthesized by a modified sol-gel method and then prepared by the impregnation method. We also fabricated dye-sensitized solar cells, which were composed of Au grating/Au-TiO2/TMPyP-SCC LbL (20 bilayers)/electrolyte/ITO substrates. Short-circuit photo-current measurements showed that Au-loaded TiO2 with grating-coupled surface plasmon excitation can enhance the short-circuit photocurrentof the fabricated cells.

PCA-L1 (principal component analysis based on L1-norm maximization) is an approximate solution of L1-PCA (PCA based on the L1-norm), and has robustness against outliers compared with traditional PCA. However, the more dimensions the feature space has, the more calculation time PCA-L1 consumes. This paper focuses on an initialization procedure of PCA-L1 algorithm, and proposes a fast method of PCA-L1 using Gram-Schmidt orthogonalization. Experimental results on face recognition show that the proposed method works faster than conventional PCA-L1 without decrease of recognition accuracy.

This paper proposes an agent-based modeling and simulation methodology for analyzing the tactical and operational effectiveness of warfare environment. To do this, we adopt the advanced agent modeling principle, HEAP (Hierarchical Encapsulation and Abstraction Principle), as well as the hierarchical modeling and simulation framework, SES/MB (System Entity Structure/Model Base). Proposed methodology is differentiated from other conventional agent-based defense M&S approaches in that; (i) it supports an intelligent hierarchical multi-agent architecture, (ii) it provides an efficient mechanism for analyzing the strategic and operational effectiveness of warfare environment between multiple platforms. The proposed methodology is successfully applied to the two by two warships warfare simulation for analyzing the tactical effectiveness.

After brief introduction of our new microscope unit with an immersion objective and ionic liquid used as a refractive index matching medium, in this paper, we describe the studies on dipole orientation imaging of single molecules under high vacuum conditions as one of the important applications of our microscope.

Face perception and recognition have attracted more attention recently in multidisciplinary fields such as engineering, psychology, neuroscience, etc. with the advances in physical/physiological measurement and data analysis technologies. In this paper, our main interest is building computational models of human face recognition based on psychological experiments. We specially focus on modeling human face recognition characteristics of average face in the dimension of distinctiveness. Psychological experiments were carried out to measure distinctiveness of face images and their results are explained by computer analysis results of the images. Two psychological experiments, 1) Classical experiment of distinctiveness rating and, 2) Novel experiment of recognition of an average face were performed. In the later experiment, we examined on how the average face of two face images was recognized by a human in a similarity test respect to the original images which were utilized for the calculation of the average face. To explain results of the psychological experiments, eigenface spaces were constructed based on Principal Component Analysis (PCA). Significant correlation was found between human and PCA based computer recognition results. Emulation of human recognition of faces is one of the expected applications of this research.

This paper proposes an alternate time-switched transmission technique for single carrier modulation system with frequency domain equalization. Additional maximal ratio combining diversity gain is obtained by adding a transmit antenna and a switch. Alternating transmit symbols result in zeros which make maximal ratio receive combining possible in the receiver. Simulation results show that it has better performance than the traditional algorithm at the expense of one additional antenna.

In this paper, through extrinsic information transfer (EXIT) band chart analysis, an adaptive iterative decoding approach (AIDA) is proposed to reduce the iterative decoding complexity and delay for finite-length differentially encoded Low-density parity-check (DE-LDPC) coded systems with multiple-symbol differential detection (MSDD). The proposed AIDA can adaptively adjust the observation window size (OWS) of the MSDD soft-input soft-output demodulator (SISOD) and the outer iteration number of the iterative decoder (consisting of the MSDD SISOD and the LDPC decoder) instead of setting fixed values for the two parameters of the considered systems. The performance of AIDA depends on its stopping criterion (SC) which is used to terminate the iterative decoding before reaching the maximum outer iteration number. Many SCs have been proposed; however, these approaches focus on turbo coded systems, and it has been proven that they do not well suit for LDPC coded systems. To solve this problem, a new SC called differential mutual information (DMI) criterion, which can track the convergence status of the iterative decoding, is proposed; it is based on tracking the difference of the output mutual information of the LDPC decoder between two consecutive outer iterations of the considered systems. AIDA using the DMI criterion can adaptively adjust the out iteration number and OWS according to the convergence situation of the iterative decoding. Simulation results show that compared with using the existing SCs, AIDA using the DMI criterion can further reduce the decoding complexity and delay, and its performance is not affected by a change in the LDPC code and transmission channel parameters.

This paper presents a new technique to smooth speech feature vectors for text-independent speaker verification using an adaptive band-pass IIR filer. The filter is designed by considering the probability density of modulation-frequency components of an M-dimensional feature vector. Each dimension of the feature vector is processed and filtered separately. Initial filter parameters, low-cut-off and high-cut-off frequencies, are first determined by the global mean of the probability densities computed from all feature vectors of a given speech utterance. Then, the cut-off frequencies are adapted over time, i.e. every frame vector, in both low-frequency and high-frequency bands based also on the global mean and the standard deviation of feature vectors. The filtered feature vectors are used in a SVM-GMM Supervector speaker verification system. The NIST Speaker Recognition Evaluation 2006 (SRE06) core-test is used in evaluation. Experimental results show that the proposed technique clearly outperforms a baseline system using a conventional RelAtive SpecTrA (RASTA) filter.