Due to the high speed mobile environment, the aeronautical Cognitive Radio (CR) communications base on the channel with the time-variant stochastic non-continuous spectrum. The traditional fading channel models, such as Rayleigh, Rice, Nakagami-m and multipath channel models, can not describe the whole property of the channels of CR communications. In this letter, the statistical channel modeling scheme for aeronautical CR communications is proposed with a M/M/s(1) queuing model, which properly describes the random spectrum occupation of the primary users, i.e. aircrafts in aeronautical communications. The proposed channel model can be easily utilized in the channel simulation to testify the validity and efficiency of the aeronautical CR communications.

Thickness of crystalline layer induced by annealing after rubbing at surface of polyimide film for liquid crystal displays was estimated to be 3--5 nm by grazing-incidence X-ray diffractions with multi incident angles. Agreement of thickness of crystalline layer with that of initially oriented layer suggests polymer orientation induced by rubbing proceeds crystallization by annealing. Furthermore, no in-plane smectic ordering in bottom 20,nm region of polyimide film was suggested.

In this paper, we propose demodulators for the Golden and Alamouti codes in amplify-and-forward (AF) cooperative communication with one relay. The proposed demodulators output exact log likelihood ratios (LLRs) with recursion based on the Jacobian logarithm. The cooperative system with the proposed demodulator for the Golden code has the benefit of efficient data transmission, while the system for the Alamouti code has low demodulation complexity. Quantitative analyses of computational complexity of the proposed demodulators are conducted. The transmission performance for various relay location and power settings is evaluated on cooperative orthogonal frequency division multiplexing (OFDM)-based wireless local area network (LAN) systems. In evaluations, the optimal relay location and power settings are found. The cooperative system with the proposed demodulators for the Golden and Alamouti codes offers 1.5 and 1.9 times larger areas where 10.8 and 5.4Mbit/s can be obtained than a non-cooperative (direct) system in a typical office environment, respectively.

In this letter, we formally present the definition of KDM-CCA1 security in public key setting, which falls in between the existing KDM-CPA and KDM-CCA2 security. We also prove that if a public key encryption scheme is CCA1 secure and has the properties of secret-key multiplication (or addition) homomorphism, and conditioned plaintext-restorability, then it is KDM-CCA1 secure w.r.t. two ensembles of functions that had been used in [15],[17], respectively. For concrete scheme, we show that the (tailored) Damgård's Elgamal scheme achieves this KDM-CCA1 security based on different assumptions.

Bandwidth aggregation (BAG) techniques have been researched for many years in an efforts to enhance throughput for multi-homed streaming service. However, despite of the considerable attention being devoted towards energy-efficient communications, the power efficiency for BAG has not been considered yet. To improve the power efficiency in multi-homed streaming service, this paper proposes Power Minimized Rate Allocation Scheme (PMRAS) with optimal rate allocation at each interface while guaranteeing an allowable packet loss rate. In developing PMRAS, we first formulate a power consumption model based on the network interface state (i.e. active and idle state). We adopt a Lagrangian algorithm to solve the convex optimization problem of power consumption. The performance results gained from a numerical analysis and simulations (NS-2) reveal that the proposed scheme offers superior performance over the existing rate allocation scheme for BAG with guaranteed required quality of service.

This paper proposes an adaptive band activity ratio control (ABC) with cascaded energy allocation (CEA) scheme to improve end-to-end spectral efficiency for two-hop amplify-and-forward orthogonal frequency division multiplexing relay systems under transmit energy constraint. Subchannel pairing (SP) based spectrum mapping maps spectral components transmitted over high gain subchannels in the source-to-relay link onto high gain subchannels of the relay-to-destination link to improve the spectral efficiency. However, SP suffers from a frame efficiency reduction due to the notification of information of spectral component order. To compensate for the deficiency of SP, the proposed scheme employs dynamic spectrum control with ABC in which spectral components are mapped onto subchannels having high channel gain in each link, while band activity ratio (BAR) is controlled to an optimal value, which is smaller than 1, so that all spectral components are transmitted over relatively high gain subchannels of the two links. To further improve the performance, energy allocation at the source node and the relay node is serially conducted based on convex optimization, and BAR is controlled to improve discrete-input continuous-output memoryless channel capacity at the relay node. In the proposed scheme, since only information of BAR needs to be notified, the notification overhead is drastically reduced compared to that in SP based spectrum mapping. Numerical analysis confirms that the proposed ABC combined with CEA significantly reduces the required notification overhead while achieving almost the same frame error rate performance compared with the SP based scheme.

This study investigated the distribution of attention to frontal space in augmented reality (AR). We conducted two experiments to compare binocular and monocular observation when an AR image was presented. According to a previous study, when participants observed an AR image in monocular presentation, they perceived the AR image as more distant than in binocular vision. Therefore, we predicted that attention would need to be shifted between the AR image and the background in not the monocular observation but the binocular one. This would enable an observer to distribute his/her visual attention across a wider space in the monocular observation. In the experiments, participants performed two tasks concurrently to measure the size of the useful field of view (UFOV). One task was letter/number discrimination in which an AR image was presented in the central field of view (the central task). The other task was luminance change detection in which dots were presented in the peripheral field of view (the peripheral task). Depth difference existed between the AR image and the location of the peripheral task in Experiment 1 but not in Experiment 2. The results of Experiment 1 indicated that the UFOV became wider in the monocular observation than in the binocular observation. In Experiment 2, the size of the UFOV in the monocular observation was equivalent to that in the binocular observation. It becomes difficult for a participant to observe the stimuli on the background in the binocular observation when there is depth difference between the AR image and the background. These results indicate that the monocular presentation in AR is superior to binocular presentation, and even in the best condition for the binocular condition the monocular presentation is equivalent to the binocular presentation in terms of the UFOV.

Strongly deterministic multithreading provides determinism for multithreaded programs even in the presence of data races. A common way to guarantee determinism for data races is to isolate threads by buffering shared memory accesses. Unfortunately, buffering all shared accesses is prohibitively costly. We propose an approach called DRDet to efficiently make data races deterministic. DRDet leverages the insight that, instead of buffering all shared memory accesses, it is sufficient to only buffer memory accesses involving data races. DRDet uses a sound data-race detector to detect all potential data races. These potential data races, along with all accesses which may access the same set of memory objects, are flagged as data-race-involved accesses. Unsurprisingly, the imprecision of static analyses makes a large fraction of shared accesses to be data-race-involved. DRDet employs two optimizations which aim at reducing the number of accesses to be sent to query alias analysis. We implement DRDet on CoreDet, a state-of-the-art deterministic multithreading system. Our empirical evaluation shows that DRDet reduces the overhead of CoreDet by an average of 1.6X, without weakening determinism and scalability.

In this paper, we propose a texture descriptor based on amplitude distribution and phase distribution of the discrete Fourier transform (DFT) of an image. One dimensional DFT is applied to all the rows and columns of an image. Histograms of the amplitudes and gradients of the phases between adjacent rows/columns are computed as the feature descriptor, which is called aggregated DFT (ADFT). ADFT can be easily combined with completed local binary pattern (CLBP). The combined feature captures both global and local information of the texture. ADFT is designed for isotropic textures and demonstrated to be effective for roughness classification of castings. Experimental results show that the amplitude part of ADFT is also discriminative in describing anisotropic textures and it can be used as a complementary descriptor of local texture descriptors such as CLBP.

Presentation slide composition is an important job for knowledge workers. Instead of starting from scratch, users tend to make new presentation slides by reusing existing ones. A primary challenge in slide reuse is to select desired materials from a collection of existing slides. The state-of-the-art solution utilizes texts and images in slides as well as file names to help users to retrieve the materials they want. However, it only allows users to choose an entire slide as a query but does not support the search for a single element such as a few keywords, a sentence, an image, or a diagram. In this paper, we investigate content-based search for a variety of elements in presentation slides. Users may freely choose a slide element as a query. We propose different query processing methods to deal with various types of queries and improve the search efficiency. A system with a user-friendly interface is designed, based on which experiments are performed to evaluate the effectiveness and the efficiency of the proposed methods.

Runtime analysis is to enhance the safety of critical systems by monitoring the change of corresponding external environments. In this paper, a modified FTA approach, making full utilization of the existing safety analysis result, is put forward to achieve runtime safety analysis. The procedures of the approach are given in detail. This approach could be widely used in safety engineering of critical systems.

This paper analyzes the transmission performances of visible light communication (VLC) based on unipolar orthogonal frequency division multiplexing (OFDM), which is compatible with intensity modulation and direct detection (IM/DD). Three existing unipolar OFDM schemes, namely DC biased optical OFDM (DCO-OFDM), asymmetrically clipped optical OFDM (ACO-OFDM), and flip-OFDM are investigated and compared. While these three schemes have been analyzed for indoor optical wireless communication (OWC) subject to the limitation on the transmit optical power, they have not been carefully investigated and compared for VLC when a large transmit power is available due to the illumination requirement, and the signal dynamic range (DR) becomes the main limitation. For the analysis, DR expressions of DCO-OFDM, ACO-OFDM, and flip-OFDM signals are first derived. Then, the bit error rate (BER) expression of each unipolar OFDM scheme is derived in terms of the DR. For data rates in the range of 1-10Mbps, under the system parameters based on typical indoor environments, DCO-OFDM is observed to outperform the other two schemes. This superiority of DCO-OFDM is in contrast with previously reported results that indicate the attractiveness of ACO-OFDM and flip-OFDM over DCO-OFDM when the transmit optical power is the main limitation. Finally, light dimming is considered to identify the illumination level below which DCO-OFDM loses this superiority.

This note presents a new approach for the robustness of Hurwitz polynomials under coefficient perturbation. The s-domain Hurwitz polynomial is transformed to the z-domain polynomial by the bilinear transformation. Then an approach based on the Rouché theorem introduced in the literature is applied to compute a crude bound for the allowable coefficient variation such that the perturbed polynomial maintains the Hurwitz stability property. Three methods to obtain improved bounds are also suggested. The results of this note are computationally more efficient than the existing direct s-domain approaches especially for polynomials of higher degree. Furthermore examples indicate that the exact bound for the coefficient variation can be obtained in some cases.

Boneh et al. proposed the new idea of pairing-based cryptography by using the composite order group instead of prime order group. Recently, many cryptographic schemes using pairings of composite order group were proposed. Miller's algorithm is used to compute pairings, and the time of computing the pairings depends on the cost of calculating the Miller loop. As a method of speeding up calculations of the pairings of prime order, the number of iterations of the Miller loop can be reduced by choosing a prime order of low Hamming weight. However, it is difficult to choose a particular composite order that can speed up the pairings of composite order. Kobayashi et al. proposed an efficient algorithm for computing Miller's algorithm by using a window method, called Window Miller's algorithm. We can compute scalar multiplication of points on elliptic curves by using a window hybrid binary-ternary form (w-HBTF). In this paper, we propose a Miller's algorithm that uses w-HBTF to compute Tate pairing efficiently. This algorithm needs a precomputation both of the points on an elliptic curve and rational functions. The proposed algorithm was implemented in Java on a PC and compared with Window Miller's Algorithm in terms of the time and memory needed to make their precomputed tables. We used the supersingular elliptic curve y2=x3+x with embedding degree 2 and a composite order of size of 2048-bit. We denote w as window width. The proposed algorithm with w=6=2·3 was about 12.9% faster than Window Miller's Algorithm with w=2 although the memory size of these algorithms is the same. Moreover, the proposed algorithm with w=162=2·34 was about 12.2% faster than Window Miller's algorithm with w=7.

Sound source localization (SSL), with a binaural input in practical environments, is a challenging task due to the effects of noise and reverberation. In psychoacoustic research field, one of the theories to explain the mechanism of human perception in such environments is the well-known equalization-cancellation (EC) model. Motivated by the EC theory, this paper investigates a binaural SSL method by integrating EC procedures into a beamforming technique. The principle idea is that the EC procedures are first utilized to eliminate the sound signal component at each candidate direction respectively; direction of sound source is then determined as the direction at which the residual energy is minimal. The EC procedures applied in the proposed method differ from those in traditional EC models, in which the interference signals in rooms are accounted in E and C operations based on limited prior known information. Experimental results demonstrate that our proposed method outperforms the traditional SSL algorithms in the presence of noise and reverberation simultaneously.

Cloud computing, a novel distributed paradigm to provide powerful computing capabilities, is usually adopted by developers and researchers to execute complicated IoT applications such as complex workflows. In this scenario, it is fundamentally important to make an effective and efficient workflow application scheduling and execution by fully utilizing the advantages of the cloud (as virtualization and elastic services). However, in the current stage, there is relatively few research for workflow scheduling in cloud environment, where they usually just bring the traditional methods directly into cloud. Without considering the features of cloud, it may raise two kinds of problems: (1) The traditional methods mainly focus on static resource provision, which will cause the waste of resources; (2) They usually ignore the performance fluctuation of virtual machines on the physical machines, therefore it will lead to the estimation error of task execution time. To address these problems, a novel mechanism which can estimate the probability distribution of subtask execution time based on background VM load series over physical machines is proposed. An elastic performance fluctuations-aware stochastic scheduling algorithm is introduced in this paper. The experiments show that our proposed algorithm can outperform the existing algorithms in several metrics and can relieve the influence of performance fluctuations brought by the dynamic nature of cloud.

A novel method for calibrating the probes used in standard measurement systems to evaluate SAR (specific absorption rate) of the radio equipment operating at frequencies over 3GHz is proposed. As for the proposed method, the electric-field distribution produced by a waveguide aperture installed in a liquid container is used to calibrate the SAR probe. The field distribution is shown to be the same as that given by a conventional calibration method by analytically deriving a closed-form expression for the field produced by the waveguide aperture with the help of the paraxial approximation. Comparing the approximated and measured distributions reveals that the closed-form expression is valid for the electric-field distribution near the central axis of the aperture. The calibration factor for a commercial SAR probe is evaluated by the proposed method and agrees well with that provided by the manufacturer of the probe.

To lengthen the operational time of mobile devices, power must be managed effectively. To achieve this objective, a Discontinuous Reception (DRX) mechanism is proposed for use in the long-term evolution (LTE) network to enable user equipment (UE) to consume power efficiently. The DRX mechanism provides parameters related to base stations such as evolved Node B (eNB) to configure and manage the transition of UEs between idle (sleep) and active states. Although these parameters can be adjusted dynamically in cooperation with the traffic scheduler, a high signaling overhead and processing load might be introduced in practical deployment if the parameters are adjusted too frequently. In this study, to examine power-saving efficiency, distinct traffic types were scheduled that were constrained by various quality of service (QoS) factors without dynamically changing the DRX parameters. The concept of burst-based scheduling is proposed, based on considering the state transitions and channel conditions of each UE, to increase power-saving efficiency while concurrently satisfying the desired QoS. Both Hypertext Transfer Protocol (HTTP) and video-stream traffic models were exhaustively simulated to examine the performance of the proposed scheme and numerous scheduling alternatives were tested to compare the proposed scheme with other schemes. The simulation results indicate that video-streaming traffic is more sensitive to the scheduling schemes than HTTP traffic. The simulation results were further analyzed in terms of traffic scheduling and parameter adjustment and the analysis results can help design future studies on power management in the LTE network.

Operating system (OS) reboots are an essential part of updating kernels and applications on laptops and desktop PCs. Long downtime during OS reboots severely disrupts users' computational activities. This long disruption discourages the users from conducting OS reboots, failing to enforce them to conduct software updates. Although the dynamic updatable techniques have been widely studied, making the system “reboot-free” is still difficult due to their several limitations. As a result, users cannot benefit from new functionality or better performance, and even worse, unfixed vulnerabilities can be exploited by attackers. This paper presents ShadowReboot, a virtual machine monitor (VMM)-based approach that shortens downtime of OS reboots in software updates. ShadowReboot conceals OS reboot activities from user's applications by spawning a VM dedicated to an OS reboot and systematically producing the rebooted state where the updated kernel and applications are ready for use. ShadowReboot provides an illusion to the users that the guest OS travels forward in time to the rebooted state. ShadowReboot offers the following advantages. It can be used to apply patches to the kernels and even system configuration updates. Next, it does not require any special patch requiring detailed knowledge about the target kernels. Lastly, it does not require any target kernel modification. We implemented a prototype in VirtualBox 4.0.10 OSE. Our experimental results show that ShadowReboot successfully updated software on unmodified commodity OS kernels and shortened the downtime of commodity OS reboots on five Linux distributions (Fedora, Ubuntu, Gentoo, Cent, and SUSE) by 91 to 98%.

In Still-to-Video (S2V) face recognition, only a few high resolution images are registered for each subject, while the probe is video clips of complex variations. As faces present distinct characteristics under different scenarios, recognition in the original space is obviously inefficient. Thus, in this paper, we propose a novel discriminant analysis method to learn separate mappings for different scenario patterns (still, video), and further pursue a common discriminant space based on these mappings. Concretely, by modeling each video as a manifold and each image as point data, we form the scenario-oriented mapping learning as a Point-Manifold Discriminant Analysis (PMDA) framework. The learning objective is formulated by incorporating the intra-class compactness and inter-class separability for good discrimination. Experiments on the COX-S2V dataset demonstrate the effectiveness of the proposed method.