In 2005, collision resistance of several hash functions was broken by Wang et al. The strategy of determining message differences is the most important part of collision attacks against hash functions. So far, many researchers have tried to analyze Wang et al.'s method and proposed improved collision attacks. Although several researches proposed improved attacks, all improved results so far were based on the same message differences proposed by Wang et al. In this paper, we propose new message differences for collision attacks on MD4 and MD5. Our message differences of MD4 can generate a collision with complexity of less than two MD4 computations, which is faster than the original Wang et al.'s attack, and moreover, than the all previous attacks. This is the first result that improves the complexity of collision attack by using different message differences from Wang et al.'s. Regarding MD5, so far, no other message difference from Wang et al.'s is known. Therefore, study for constructing method of other message differences on MD5 should be interesting. Our message differences of MD5 generates a collision with complexity of 242 MD5 computations, which is slower than the latest best attack. However, since our attack needs only 1 bit difference, it has some advantages in terms of message freedom of collision messages.

An injection-locked clock recovery circuit (CRC) with quadrature outputs based on multiplexed oscillator is presented. The CRC can operate at a half-rate speed to provide an adequate locking range with reasonable jitter and power consumption because both clock edges sample the data waveforms. Implemented by 0.18-µm CMOS technique, experimental results demonstrate that it can achieve the phase noise of the recovered clock about -121.55 dBc/Hz at 100-kHz offset and -129.58 dBc/Hz at 1-MMz offset with 25 MHz lock range, while operating at the input data rate of 1.55 Gb/s.

Auto-calibration for structure and motion recovery can be used for match move where the goal is to insert synthetic 3D objects into real scenes and create views as if they were part of the real scene. However, most auto-calibration methods for multi-views utilize bundle adjustment with non-linear optimization, which requires a very good starting approximation. We propose a novel key-frame selection measurement and LMedS (Least Median of Square)-based approach to estimate scene structure and motion from image sequences captured with a hand-held camera. First, we select key-frames considering the ratio of number of correspondences and feature points, the homography error and the distribution of corresponding points in the image. Then, by using LMedS, we reject erroneous frames among the key-frames in absolute quadric estimation. Simulation results demonstrated that the proposed method can select suitable key-frames efficiently and achieve more precise camera pose estimation without non-linear optimization.

Shot transition detection is a core technology in video browsing, indexing systems and information retrieval. In this paper we propose a dissolve detection algorithm using the characteristics of edge in MPEG compressed video. Using the intensity change information of edge pixels obtained by Sobel edge detector, we detect the location of a dissolve and its precise duration. We also present a new reliable method to eliminate the false dissolves. The proposed algorithm is tested in various types of videos, and the experimental results show that the proposed algorithm is effective and robust.

The analysis of multiband quantum transport simulation in double-gate metal oxide semiconductor field effects transistors (DG-MOSFETs) is performed based on a non-equilibrium Green's function (NEGF) formalism coupled self-consistently with the Poisson equation. The empirical sp3s* tight binding approximation (TBA) with nearest neighbor coupling is employed to obtain a realistic multiband structure. The effects of non-parabolic bandstructure as well as anisotropic features of Si are studied and analyzed. As a result, it is found that the multiband simulation results on potential and current profiles show significant differences, especially in higher applied bias, from those of conventional effective mass model.

By diversifying processor architecture, computer software is expected to be more resistant to plagiarism, analysis, and attacks. This study presents a new method to diversify instruction set architecture (ISA) by utilizing the redundancy in the instruction set. Our method is particularly suited for embedded systems implemented with FPGA technology, and realizes a genuine instruction set randomization, which has not been provided by the preceding studies. The evaluation results on four typical ISAs indicate that our scheme can provide a far larger degree of freedom than the preceding studies. Diversified processors based on MIPS architecture were actually implemented and evaluated with Xilinx Spartan-3 FPGA. The increase of logic scale was modest: 5.1% in Specialized design and 3.6% in RAM-mapped design. The performance overhead was also modest: 3.4% in Specialized design and 11.6% in RAM-mapped design. From these results, our scheme is regarded as a practical and promising way to secure FPGA-based embedded systems.

In this paper, we propose and demonstrate a novel type of PCF that has two cladding layers with Ge rods at the center core. We numerically show that it is possible to design a single mode PCF with large effective area greater than 200 µm2 over the whole wavelength above 1.2 µm. The proposed large mode area PCF (LMA-PCF) exhibits a high negative dispersion coefficient from -186 to -158 [ps/(nm-km)] in all wavelengths ranging from 1.2 µm to 1.8 µm. Effective single mode operation of LMA-PCF is confimed for the entire band of interest.

Self embedding watermarking is a technique used for tamper detection, localization and recovery. This letter proposes a novel self embedding scheme, in which the halftone version of the host image is exploited as a watermark, instead of a JPEG-compressed version used in most existing methods. Our scheme employs a pixel-wise permuted and embedded mechanism and thus overcomes some common drawbacks of the previous methods. Experimental results demonstrate our technique is effective and practical.

The concept of placing enormous Solar Power Satellite (SPS) systems in space represents one of a handful of new technological options that might provide large scale, environmentally clean base load power to terrestrial markets. Recent advances in space exploration have shown a great need for antennas with high resolution, high gain and low side lobe level (SLL). The last characteristic is of paramount importance especially for the Microwave Power Transmission (MPT) in order to achieve higher transmitting efficiency (TE) and higher beam collection efficiency (BCE). In order to achieve low side lobe levels, statistical methods play an important role. Various interesting properties of a large antenna arrays with randomly, uniformly and combined spacing of elements have been studied, especially the relationship between the required number of elements and their appropriate spacing from one viewpoint and the desired SLL, the aperture dimension, the beamwidth and TE from the other. We propose a new unified approach in searching for reducing SLL by exploiting the interaction of deterministic and stochastic workspaces of proposed algorithms. Our models indicate the side lobe levels in a large area around the main beam and strongly reduce SLL in the entire visible range. A new concept of designing a large antenna array system is proposed. Our theoretic study and simulation results clarify how to deal with the problems of side lobes in designing a large antenna array, which seems to be an important step toward the realization of future SPS/MPT systems.

A concurrent model of computation and a language based on the model for bit-level operation are useful for developing asynchronous and concurrent programs compositionally, which frequently use bit-level operations. Some examples are programs for video games, hardware emulation (including virtual machines), and signal processing. However, few models and languages are optimized and oriented to bit-level concurrent computation. We previously developed a visual programming language called A-BITS for bit-level concurrent programming. The language is based on a dataflow-like model that computes using processes that provide serial bit-level operations and FIFO buffers connected to them. It can express bit-level computation naturally and develop compositionally. We then devised a concurrent computation model called APEC (Asynchronous Program Elements Connection) for bit-level concurrent computation. This model enables precise and formal expression of the process of computation, and a notion of primitive program elements for controlling and operating can be expressed synthetically. Specifically, the model is based on a notion of uniform primitive processes, called primitives, that have three terminals and four ordered rules at most, as well as on bidirectional communication using vehicles called carriers. A new notion is that a carrier moving between two terminals can briefly express some kinds of computation such as synchronization and bidirectional communication. The model's properties make it most applicable to bit-level computation compositionally, since the uniform computation elements are enough to develop components that have practical functionality. Through future application of the model, our research may enable further research on a base model of fine-grain parallel computer architecture, since the model is suitable for expressing massive concurrency by a network of primitives.

In this article, we discuss the security of double-block-length (DBL) hash functions against the free-start collision attack. We focus on the DBL hash functions composed of compression functions of the form F(x) = (f(x), f(p(x))), where f is a smaller compression function and p is a permutation. We first show, in the random oracle model, that a significantly good upper bound can be obtained on the success probability of the free-start collision attack with sufficient conditions on p and the set of initial values. We also show that a similar upper bound can be obtained in the ideal cipher model if f is composed of a block cipher.

The combination of deliberate clipping and an adaptive symbol selection scheme (ASSS) can be used to reduce the peak to average power ratio (PAPR) for Orthogonal Frequency Division Multiplexing (OFDM) signals. The probability density function (pdf) of a sample's amplitude of an adaptively selected OFDM signal without over-sampling has been considered to be approximately equal to the Rayleigh pdf. In this letter, we derive the exact pdf showing the relationship between the probability distribution of the sample's amplitude and the number of candidate OFDM symbols for ASSS. The use of the newly derived pdf can measure the effect of deliberate clipping on the adaptively selected OFDM signal more accurately.

In this paper we analyze the characteristics of vehicle mobility and propose a novel Mobility Prediction Progressive Routing (MP2R) protocol for Inter-Vehicle Communication (IVC) that is based on cross-layer design. MP2R utilizes the additional gain provided by the directional antennas to improve link quality and connectivity; interference is reduced by the directional transmission. Each node learns its own position and speed and that of other nodes, and performs position prediction. (i) With the predicted progress and link quality, the forwarding decision of a packet is locally made, just before the packet is actually transmitted. In addition the load at the forwarder is considered in order to avoid congestion. (ii) The predicted geographic direction is used to control the beam of the directional antenna. The proposed MP2R protocol is especially suitable for forwarding burst traffic in highly mobile environments. Simulation results show that MP2R effectively reduces Packet Error Ratio (PER) compared with both topology-based routing (AODV [1], FSR [2]) and normal progressive routing (NADV [18]) in the IVC scenarios.

In this paper, an architecture of MIMO mesh network which avoids co-channel interference and supplies link multiplexing simultaneously, namely MIMO spatial spectrum sharing, is proposed. As a MIMO transmission scheme, linear (such as zero-forcing) and nonlinear (such as dirty paper coding and successive interference cancellation) MIMO algorithm are developed for the proposed mesh network. It is found from numerical analysis that the proposed MIMO mesh network achieves significantly higher channel capacity than that of conventional mesh networks.

In this paper, we consider a network of N identical IEEE 802.11 DCF (Distributed Coordination Function) terminals with RTS/CTS mechanism, each of which is assumed to be saturated. For performance analysis, we propose a simple and efficient mathematical model to derive the statistical characteristics of the network such as the inter-transmission time of packets in the network and the service time (the inter-transmission time of successful packet transmissions) of the network. Numerical results and simulations are provided to validate the accuracy of our model and to study the performance of the IEEE 802.11 DCF network.

We propose a neurodynamical approach to a large-scale optimization problem in Cognitive Wireless Clouds, in which a huge number of mobile terminals with multiple different air interfaces autonomously utilize the most appropriate infrastructure wireless networks, by sensing available wireless networks, selecting the most appropriate one, and reconfiguring themselves with seamless handover to the target networks. To deal with such a cognitive radio network, game theory has been applied in order to analyze the stability of the dynamical systems consisting of the mobile terminals' distributed behaviors, but it is not a tool for globally optimizing the state of the network. As a natural optimization dynamical system model suitable for large-scale complex systems, we introduce the neural network dynamics which converges to an optimal state since its property is to continually decrease its energy function. In this paper, we apply such neurodynamics to the optimization problem of radio access technology selection. We compose a neural network that solves the problem, and we show that it is possible to improve total average throughput simply by using distributed and autonomous neuron updates on the terminal side.

We propose an adaptive SLM scheme based on peak observation for PAPR reduction of OFDM signals. The proposed scheme is composed of three steps: peak scaling, sequence selection, and SLM procedures. In the first step, the peak signal samples in the IFFT outputs of the original input sequence are scaled down. In the second step, the sub-carrier positions where the power difference between the original input sequence and the FFT output of the scaled signal is large, are identified. Then, the phase sequences having the maximum number of phase-reversed sequence words only for these positions are selected. Finally, the generic SLM procedure is performed by using only the selected phase sequences for the original input sequence. Simulation results show that the proposed scheme significantly reduce the complexity in terms of IFFT and PAPR calculation than the conventional SLM, while maintaining the PAPR reduction performance.

In this paper, we propose a soft decision based cooperative sensing method for cognitive radio (CR) networks for opportunistic frequency usage. To identify unused frequency, CR should exploit sensing technique to detect presence or absence of primary user and use this information to opportunistically provide communication among secondary users while performance of primary user should not be deteriorated by the secondary users. Because of multipath fading or shadowing, the detection of primary users may be significantly difficult. For this problem, cooperative sensing (CS), where gathered observations obtained by multiple secondary users is utilized to achieve higher performance of detection, has been investigated. We design a soft decision based CS analytically and analyze the detector in several situations, i.e., signal model where single-carrier case and multi-carrier case are assumed and two scenarios; in the first scenario, SNR values of secondary users are totally equal and in the second scenario, a certain SNR difference between secondary users is assumed. We present numerical results as follows. The first scenario shows that there is little difference between the signal models in terms of detection performance. The second scenario shows that CS is superior to non-cooperative sensing. In addition, we presents that detection performance of soft decision based CS outperform detection performance of hard decision based CS.

This paper proposes a novel fiber endface preparation tool for optical fiber joints that employs thermal surface cleaning and thermal endface cutting. This tool has great advantages in terms of fiber endface preparation time, and fiber endface stability when fiber is cut repeatedly. Stable thermal surface cleaning and thermal endface cutting are achieved by selecting suitable heating conditions. The fiber endface preparation time can be reduced to 50% of that required with conventional tools. The fiber endface stability obtained using thermal cutting is more than five times better than that obtained with the conventional tool using a blade.

Outage performance of cognitive radios is analyzed in this paper. The scenario under consideration requires the cognitive radio to sense whether the primary user (PU) link is free (i.e. a spectrum hole exists) before making an active transmission using that link. Multiple antennas are available at the cognitive radio link to provide array gains at the sensing stage. We derive a closed-form expression of the outage probability for cognitive transmission by classifying it into several cases. A sensing threshold is deduced according to the PU arrival model illustrated in this paper. Simulation results verify our analysis.