Due to the growing popularity of High Dynamic Range (HDR) images and HDR displays, a large amount of existing Low Dynamic Range (LDR) images are required to be converted to HDR format to benefit HDR advantages, which give rise to some LDR to HDR algorithms. Most of these algorithms especially tackle overexposed areas during expanding, which is the potential to make the image quality worse than that before processing and introduces artifacts. To dispel these problems, we present a new LDR to HDR approach, unlike the existing techniques, it focuses on avoiding sophisticated treatment to overexposed areas in dynamic range expansion step. Based on a separating principle, firstly, according to the familiar types of overexposure, the overexposed areas are classified into two categories which are removed and corrected respectively by two kinds of techniques. Secondly, for maintaining color consistency, color recovery is carried out to the preprocessed images. Finally, the LDR image is expanded to HDR. Experiments show that the proposed approach performs well and produced images become more favorable and suitable for applications. The image quality metric also illustrates that we can reveal more details without causing artifacts introduced by other algorithms.

Identification of early aspects is the critical problem in aspect-oriented requirement engineering. But the representation of crosscutting concerns is various, which makes the identification difficult. To address the problem, this paper proposes the AspectQuery method based on goal model. We analyze four kinds of goal decomposition models, then summarize the main factors about identification of crosscutting concerns and conclude the identification rules based on a goal model. A goal is crosscutting concern when it satisfies one of the following conditions: i) the goal is contributed to realize one soft-goal; ii) parent goal of the goal is candidate crosscutting concern; iii) the goal has at least two parent goals. AspectQuery includes four steps: building the goal model, transforming the goal model, identifying the crosscutting concerns by identification rules, and composing the crosscutting concerns with the goals affected by them. We illustrate the AspectQuery method through a case study (a ticket booking management system). The results show the effectiveness of AspectQuery in identifying crosscutting concerns in the requirement phase.

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.

We demonstrated the reduced surface roughness of poly (3-hexylthiophene) (P3HT):(6,6)-phenyl-C61-butyric acid methyl ester (PCBM) thin films with different ratios fabricated by the electrospray deposition (ESD) method. Aggregated structures were observed at the lower voltage, and the uniformity became bad at the higher voltage. Anyway, the minimum root mean square (RMS) roughness was 1.46 nm by optimizing the applied voltage.

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.

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.

The multivariate public key cryptosystem (MPKC), which is based on the problem of solving a set of multivariate systems of quadratic equations over a finite field, is expected to be secure against quantum attacks. Although there are several existing schemes in MPKC that survived known attacks and are much faster than RSA and ECC, there have been few discussions on security against physical attacks, aside from the work of Okeya et al. (2005) on side-channel attacks against Sflash. In this study, we describe general fault attacks on MPKCs including Big Field type (e.g. Matsumoto-Imai, HFE and Sflash) and Stepwise Triangular System (STS) type (e.g. UOV, Rainbow and TTM/TTS). For both types, recovering (parts of) the secret keys S,T with our fault attacks becomes more efficient than doing without them. Especially, on the Big Field type, only single fault is sufficient to recover the secret keys.

This letter discusses with cryptanalysis with impossible differentials. After Biham et al. presented an attack on Skipjack, the applications to many ciphers were done, and we think that the attack is one of the most effective tool to cryptanalyze a block cipher. However, unfortunately, there is no construction method that provably resists the attack. This letter first introduces the measure that can evaluate the resistance against cryptanalysis with impossible differentials. Then, we propose a construction that resists cryptanalysis with impossible differentials. Moreover, a cipher that is based on the construction also provably resists differential cryptanalysis and linear cryptanalysis.

Cloud computing is an emerging computing paradigm that may have a significant impact on various aspects of the development of information infrastructure. In a Cloud environment, different types of network resources need to be virtualized as a series of service components by network virtualization, and these service components should be further composed into Cloud services provided to end users. Therefore Quality of Service (QoS) aware service composition plays a crucial role in Cloud service provisioning. This paper addresses the problem on how to compose a sequence of service components for QoS guaranteed service provisioning in a virtualization-based Cloud computing environment. The contributions of this paper include a system model for Cloud service provisioning and two approximation algorithms for QoS-aware service composition. Specifically, a system model is first developed to characterize service provisioning behavior in virtualization-based Cloud computing, then a novel approximation algorithm and a variant of a well-known QoS routing procedure are presented to resolve QoS-aware service composition. Theoretical analysis shows that these two algorithms have the same level of time complexity. Comparison study conducted based on simulation experiments indicates that the proposed novel algorithm achieves better performance in time efficiency and scalability without compromising quality of solution. The modeling technique and algorithms developed in this paper are general and effective; thus are applicable to practical Cloud computing systems.

Recently, some cryptographic primitives have been described that are based on the supposed hardness of finding an isogeny between two supersingular elliptic curves. As a part of such a primitive, Charles et al. proposed an algorithm for computing sequences of 2-isogenies. However, their method involves several redundant computations. We construct simple algorithms without such redundancy, based on very compact descriptions of the 2-isogenies. For that, we use some observations on 2-torsion points.

At Eurocrypt'2006, Lu et al. proposed a pairing based verifiably encrypted signature scheme (the LOSSW-VES scheme) without random oracles. In this letter, we show that the LOSSW-VES scheme does not have opacity against rogue-key attacks.

We propose a new analytical method for a composite dielectric grating embedded with conducting strips using scattering factors in the shadow theory. The scattering factor in the shadow theory plays an important role instead of the conventional diffraction amplitude. By specifying the relation between scattering factors and spectral-domain Green's functions, we derive expressions of the Green's functions directly for unit surface electric and magnetic current densities, and apply the spectral Galerkin method to our formulation. From some numerical results, we show that the expressions of the Green's functions are valid, and analyze scattering characteristics by composite gratings.

Electromagnetic emissions leak confidential data of cryptographic devices. Electromagnetic Analysis (EMA) exploits such emission for cryptanalysis. The performance of EMA dramatically decreases when correlated noise, which is caused by the interference of clock network and exhibits strong correlation with encryption signal, is present in the acquired EM signal. In this paper, three techniques are proposed to reduce the correlated noise. Based on the observation that the clock signal has a high variance at the signal edges, the first technique: single-sample Singular Value Decomposition (SVD), extracts the clock signal with only one EM sample. The second technique: multi-sample SVD is capable of suppressing the clock signal with short sampling length. The third one: averaged subtraction is suitable for estimation of correlated noise when background samplings are included. Experiments on the EM signal during AES encryption on the FPGA and ASIC implementation demonstrate that the proposed techniques increase SNR as much as 22.94 dB, and the success rates of EMA show that the data-independent information is retained and the performance of EMA is improved.

In this paper, we propose a wireless network coding diversity technique based on hybrid amplify-and-forward/decode-and-forward relay method employing adaptive power control for two-hop wireless networks in order to improve relay node position flexibility. Wireless network coding diversity based on hybrid relay method selects either modulation symbol level wireless network coding diversity or bit sequence level wireless network coding diversity as its wireless network coding diversity scheme according to the cyclic redundancy check result at the relay node. Moreover, the adaptive power control scheme proposed here controls the relay node's transmit power according to its position. Computer simulations verify that wireless network coding diversity based on hybrid relay method employing the adaptive power control scheme can expand the area wherein the relay node can be located while satisfying the required communication quality by 4.56 times compared to the conventional wireless network coding diversity scheme. Therefore, we confirm that our proposed scheme can increase relay node position flexibility.

In this paper, we have addressed the problem of ordering transactions in network-on-chips (NoCs) for post-silicon validation. The main idea is to extract the order of the transactions from the local partial orders in each NoC tile based on a set of “happened-before” rules, assuming transactions do not have a timestamp. The assumption is based on the fact that implementation and usage of a global time as timestamp in such systems may not be practical or efficient. When a new transaction is received in a tile, we send special messages to the neighboring tiles to inform them regarding the new transaction. The process of sending those special messages continues recursively in all the tiles that receive them until another such special message is detected. This way, we relate local orders of different tiles with each other. We show that our method can reconstruct the correct transaction orders when communication delays are deterministic. We have shown the effectiveness of our method by correctly ordering the transaction in NoCs with mesh and torus topologies with different sizes from 5*5 to 9*9. Also, we have implemented the proposed method in hardware to show its feasibility.

A parameterization of perfect sequences over composition algebras over the real number field is presented. According to the proposed parameterization theorem, a perfect sequence can be represented as a sum of trigonometric functions and points on a unit sphere of the algebra. Because of the non-commutativity of the multiplication, there are two definitions of perfect sequences, but the equivalence of the definitions is easily shown using the theorem. A composition sequence of sequences is introduced. Despite the non-associativity, the proposed theorem reveals that the composition sequence from perfect sequences is perfect.

Post-silicon tuning is attracting a lot of attention for coping with increasing process variation. However, its tuning cost via testing is still a crucial problem. In this paper, we propose tuning-friendly body bias clustering with multiple bias voltages. The proposed method provides a small set of compensation levels so that the speed and leakage current vary monotonically according to the level. Thanks to this monotonic leveling and limitation of the number of levels, the test-cost of post-silicon tuning is significantly reduced. During the body bias clustering, the proposed method explicitly estimates and minimizes the average leakage after the post-silicon tuning. Experimental results demonstrate that the proposed method reduces the average leakage by 25.3 to 51.9% compared to non clustering case. In a test case of four clusters, the number of necessary tests is reduced by 83% compared to the conventional exhaustive test approach. We reveal that two bias voltages are sufficient when only a small number of compensation levels are allowed for test-cost reduction. We also give an implication on how to synthesize a circuit to which post-silicon tuning will be applied.

We focus on the cooperative mobile positioning based on the received signal strength for heterogeneous environments. We use the least squares method to estimate the channel attenuation coefficients, and hyperbolic method to determine the position. For increasing accuracy, we use different weighting to the adjacent users' data in the attenuation coefficients estimation.

Solving image recovery problems requires the use of some efficient regularizations based on a priori information with respect to the unknown original image. Naturally, we can assume that an image is modeled as the sum of smooth, edge, and texture components. To obtain a high quality recovered image, appropriate regularizations for each individual component are required. In this paper, we propose a novel image recovery technique which performs decomposition and recovery simultaneously. We formulate image recovery as a nonsmooth convex optimization problem and design an iterative scheme based on the alternating direction method of multipliers (ADMM) for approximating its global minimizer efficiently. Experimental results reveal that the proposed image recovery technique outperforms a state-of-the-art method.

We introduce an efficient fully simulatable construction of oblivious transfer based on the McEliece assumptions in the common reference string model. This is the first efficient fully simulatable oblivious protocol based on coding assumptions. Moreover, being based on the McEliece assumptions, the proposed protocol is a good candidate for the post-quantum scenario.