In 2010, Guo and Zhang proposed a group key agreement protocol based on the chaotic hash function. This letter points out that Guo-Zhang's protocol is still vulnerable to off-line password guessing attacks, stolen-verifier attacks and reflection attacks.

In this paper, we consider multiple source and destination antennas based on relay selection scheme to improve the end-to-end outage performance for decode-and-forward cooperative networks. We derive an exact closed-form expression of the outage probability for the proposed system over a Rayleigh fading channel and describe the diversity-multiplexing tradeoff of the system. We then analyze the effects of the number of source and destination antennas on the outage probabilities and diversity-multiplexing tradeoffs.

We have previously proposed a howling canceller which cancels howling by using a cascade notch filter designed from a distance between a loudspeaker and a microphone. This method utilizes a pilot signal to estimate the distance. In this paper, we introduce two methods into the distance-based howling canceller to improve speech quality. The first one is an adaptive cascade notch filter which adaptively adjusts the nulls to eliminate howling and to keep speech components. The second one is a silent pilot signal whose frequencies exist in the ultrasonic band, and it is inaudible while on transmission. We implement the proposed howling canceller on a DSP to evaluate its capability. The experimental results show that the proposed howling canceller improves speech quality in comparison to the conventional one.

In time division multiple access (TDMA)-based wireless mesh networks, interference relationships should be considered when time slots are assigned to links. In graph theory-based time slot assignment algorithms, the protocol interference model is widely used to determine radio interference information, although it is an inaccurate model of actual radio interference. On the other hand, the signal-to-interference-plus-noise-ratio model (SINR model) gives more accurate interference relationships but is difficult to apply to time slot assignment algorithms since the radio interference information cannot be determined before time slot assignment. In this paper, we investigate the effect of the parameters of the protocol interference model on the accuracy of the interference relationships determined using this model. Specifically, after assigning time slots to links based on the protocol interference model with various interference ratios, which is the major parameter of the protocol interference model, we compare the interference relationship among links in the protocol interference and SINR models. Through simulation experiments, we show that accuracy of the protocol interference model is improved by up to 15% by adjusting the interference ratios of the protocol interference model.

We propose a simple approximate model for unslotted opportunistic spectrum access networks under nonsaturation conditions. The main simplification we introduce is that all secondary users, except a tagged one, in nonsaturated setting can be approximated by saturated ones with a scaled version of backoff interval. We analyze the approximate model and verify the model using simulations.

Measuring the relational similarity between word pairs is important in numerous natural language processing tasks such as solving word analogy questions, classifying noun-modifier relations and disambiguating word senses. We propose a supervised classification method to measure the similarity between semantic relations that exist between words in two word pairs. First, each pair of words is represented by a vector of automatically extracted lexical patterns. Then a binary Support Vector Machine is trained to recognize word pairs with similar semantic relations to a given word pair. To train and evaluate the proposed method, we use a benchmark dataset that contains 374 SAT multiple-choice word-analogy questions. To represent the relations that exist between two word pairs, we experiment with 11 different feature functions, including both symmetric and asymmetric feature functions. Our experimental results show that the proposed method outperforms several previously proposed relational similarity measures on this benchmark dataset, achieving an SAT score of 46.9.

The air traffic situational awareness is an essential factor for flight safety and efficiency. Today, pilots have only two methods for situational awareness, through visual acquisition or with traffic information via voice messages from Air Traffic Controllers. These methods have limitations in reducing aircraft separation because of their delay in acquiring traffic. To improve the acquisition of traffic information, airborne surveillance with ADS-B/TIS-B has been proposed. This paper reports on the prototype TIS-B system developed by ENRI and on the results of evaluations with flight testing.

Solution-based organic field-effect transistors (OFETs) with low parasitic capacitance have been fabricated using a self-aligned method. The self-aligned processes using a cross-linking polymer gate insulator allow fabricating electrically stable polymer OFETs with small overlap area between the source-drain electrodes and the gate electrode, whose frequency characteristics have been investigated by impedance spectroscopy (IS). The IS of polymer OFETs with self-aligned electrodes reveals frequency-dependent channel formation process and the frequency response in FET structure.

In this letter, we propose a power allocation scheme to optimize the ergodic secrecy rate of multiple-input single-output (MISO) fading wiretap channels with a probabilistic constraint, using the statistical channel state information (CSI) of the eavesdropper (CSI-E). The analytical expressions of the false secrecy probability are derived and used as constraints in the rate maximization problem. Moreover, we obtain a suboptimal solution by formulating the power allocation problem as a Rayleigh quotient problem.

In non-cooperative scenarios, the estimation of direct sequence spread spectrum (DS-SS) signals has to be done in a blind manner. In this letter, we consider the spreading sequence estimation problem for DS-SS signals. First, the maximum likelihood estimate (MLE) of spreading sequence is derived, then a semidefinite relaxation (SDR) approach is proposed to cope with the exponential complexity of performing MLE. Simulation results demonstrate that the proposed approach provides significant performance improvements compared to existing methods, especially in the case of low numbers of data samples and low signal-to-noise ratio (SNR) situations.

We propose a data transmission method for resonant wireless power transmission systems. In order to transmit data, we use the coils originally designed for power transmission, no additional antennas are required. We focus on uplink data transmission and adopt the load modulation technique. This configuration yields mid-range data transmission without transmitting power. In addition, the proposal enables simultaneous power feeding and uplink data transmission. We make a prototype demonstrating resonant wireless power transmission and measure its S-parameter under some load conditions. The results confirm the potential of load modulation in supporting uplink data transmission. Additionally, the results are elucidated by analyzing an equivalent circuit. Measured S-parameter and equivalent circuit response are found to be similar.

This letter considers a sum-rate maximization problem with user scheduling wherein each user has a minimum-rate requirement in multiple-input-multiple-output broadcast channel. The multiuser strategy used in the user scheduling is a joint transceiver scheme with block diagonal geometric mean decomposition. Since optimum solution to the user scheduling problem generally requires exhaustive search, we propose a suboptimum user scheduling algorithm with each user's minimum-rate requirement as the main constraint. In order to satisfy maximum sum-rate and minimum-rate constraints simultaneously, we additionally consider power allocation for scheduled users. Simulation results show that the proposed user scheduling algorithm, together with the user power allocation, achieves sum-rate close to the exhaustive search, while also guarantees minimum-rate requirement of each user.

With the rapid development and proliferation of the Internet, cyber attacks are increasingly and continually emerging and evolving nowadays. Malware – a generic term for computer viruses, worms, trojan horses, spywares, adwares, and bots – is a particularly lethal security threat. To cope with this security threat appropriately, we need to identify the malwares' tendency/characteristic and analyze the malwares' behaviors including their classification. In the previous works of classification technologies, the malwares have been classified by using data from dynamic analysis or code analysis. However, the works have not been succeeded to obtain efficient classification with high accuracy. In this paper, we propose a new classification method to cluster malware more effectively and more accurately. We firstly perform dynamic analysis to automatically obtain the execution traces of malwares. Then, we classify malwares into some clusters using their characteristics of the behavior that are derived from Windows API calls in parallel threads. We evaluated our classification method using 2,312 malware samples with different hash values. The samples classified into 1,221 groups by the result of three types of antivirus softwares were classified into 93 clusters. 90% of the samples used in the experiment were classified into 20 clusters at most. Moreover, it ensured that 39 malware samples had characteristics different from other samples, suggesting that these may be new types of malware. The kinds of Windows API calls confirmed the samples classified into the same cluster had the same characteristics. We made clear that antivirus softwares named different name to malwares that have same behavior.

Due to the lack of end-to-end paths between the communication source and destination in the Disruption Tolerant Network (DTN), its routing employs the store-carry-and-forward mechanism. In order to provide communication service in the DTN where there is only intermittent connectivity between nodes, a variety of epidemic-style routing algorithms have been proposed to achieve high message delivery probability at the cost of energy consumption. In this contribution, we investigate the problem of optimal multi-frame content transmission. By formulating the optimization problem with a Markov model, we derive the optimal policies under the two conditions of with and without energy constraint. We also investigate the performance of the proposed optimal policies through extensive numerical analyses, and conclude that the optimal policies give the best performance and the energy constraint critically degrades the system performance in the multi-frame content transmission.

In this paper, we present a cognitive relay network with two primary transceivers that communicate via several distributed relay terminals. Spectrum sensing is deployed at the relays to sense the absence/presence of the primary transceivers based on energy detection. The primary network utilizes a two-step two-way amplify-and-forward (AF) scheme by using the cognitive radio (CR) terminals as its relay nodes when the primary network is not in operation, in contrast, the CRs communicate with their own base station (BS). In the first relaying step, the primary transceivers send their signal to the CRs/relays. Distributed beamforming is then performed in the second relaying step. Our aim is to set the beamforming weights so as to minimize the total power dissipated in the relay network while satisfying a target signal-to-noise ratio (SNR) at the primary transceivers and at the cognitive BS. This is achieved by solving an optimization problem that we formulate as a nonconvex quadratically constrained quadratic program (QCQP). This problem is solved efficiently by semidefinite relaxation (SDR) and Lagrangian duality. Simulation results are provided to demonstrate the superiority of our proposed technique, compared to classical beamforming techniques, in terms of power reduction.

In this paper, N-CSK (N parallel Codes Shift Keying) using modified pseudo orthogonal M-sequence sets (MPOMSs) to realize the parallel combinatory spread spectrum (PC/SS) communication system for the optical communications is proposed. Moreover, the upper bound of data transmission rate and the bit error rate (BER) performance of this N-CSK system using the chip-level detection are evaluated through theoretical analysis by taking into account the scintillation, background-noise, avalanche photo-diode (APD) noise, thermal noise, and signal dependence noise. It is shown that the upper bound of data transmission rate of the proposed system is better than those of OOK/CDM and SIK/CDM. Moreover, the upper bound of data transmission rate of the proposed system can achieve about 1.5 [bit/chip] when the code length of MPOMS is 64 [chip].

We have succeeded in developing high-performance p-type of organic semiconductors with phenylethynyl groups, which have high filed-effect mobilities (>3 cm2V-1s-1) by improving molecular planarity. A single crystal of the organic semiconductors has a herringbone structure. It plays an important role for carrier transport. In addition, we found that they had lower contact resistances to Au electrodes as well. Then, we used the materials for the carrier injection layer deposited onto another organic semiconductor we developed recently, which achieved a high field-effect mobility, and a low threshold voltage (Vth).

The involvement of IEEE 802.15.4 Wireless Sensor Networks (WSNs) in diverse applications has made the realistic analysis of sensor power dissipation in distributed network environments an essential research issue. In this paper, we propose and thoroughly analyze a power dissipation model for Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA) based IEEE 802.15.4 distributed multi-hop WSNs. Our model takes the loss rate of frames, neighbor sensors density in communication range of a sensor, number of hops, distance of source to the sink, and density of the network into account. We evaluate the impact of these factors on overall power dissipation. We also perform comprehensive analysis of overheads caused by message routing through multi-hop distributed networks. We validate our proposed model through Monte Carlo simulations. Results show that our power dissipation model is more realistic compared to other proposed models in terms of accuracy and multiplicity of the environments.

In this letter, an improved triple-tunable frequency synthesizer structure to achieve both high frequency resolution and fast switching speed without degradation of spurious signals (spurs) level performance is proposed. According to this structure, a high performance millimeter-wave frequency synthesizer with low spurious, low phase noise, and fast switching speed, is developed. This synthesizer driven by the direct digital synthesizer (DDS) AD9956 can adjust the output of a DDS and frequency division ratios of two variable frequency dividers (VFDs) to move the spurious components outside the loop bandwidth of the phase-locked loop (PLL). Moreover, the ADF4252 based microwave PLL can further suppress the phase noise. Experimental results from the implemented synthesizer show that remarkable performance improvements have been achieved.

Nowadays, pedestrian recognition for automotive and security applications that require accurate recognition in images taken from distant observation points is a recent challenging problem in the field of computer vision. To achieve accurate recognition, both detection and tracking must be precise. For detection, some excellent schemes suitable for pedestrian recognition from distant observation points are proposed, however, no tracking schemes can achieve sufficient performance. To construct an accurate tracking scheme suitable for pedestrian recognition from distant observation points, we propose a novel pedestrian tracking scheme using multiple cues: HSV histograms and HOG features. Experimental results show that the proposed scheme can properly track a target pedestrian where tracking schemes using only a single cue fails. Moreover, we implement the proposed scheme on NVIDIA® TeslaTM C1060 processor, one of the latest GPU, to achieve real-time processing of the proposed scheme. Experimental results show that computation time required for tracking of a frame by our implementation is reduced to 8.80 ms even though Intel® CoreTM i7 CPU 975 @ 3.33 GHz spends 111 ms.