In this letter, we present an efficient method for high quality surface reconstruction from simulation data of smoothed particles hydrodynamics (SPH). For computational efficiency, instead of computing scalar field in overall particle sets, we only construct scalar field around fluid surfaces. Furthermore, an adaptive scalar field model is proposed, which adaptively adjusts the smoothing length of ellipsoidal kernel by a constraint-correction rule. Then the isosurfaces are extracted from the scalar field data. The proposed method can not only effectively preserve fluid details, such as splashes, droplets and surface wave phenomena, but also save computational costs. The experimental results show that our method can reconstruct the realistic fluid surfaces with different particle sets.

Critical infrastructures are falsely believed to be safe when they are isolated from the Internet. However, the recent appearance of Stuxnet demonstrated that isolated networks are no longer safe. We observe that a better intrusion detection scheme can be established based on the unique features of critical infrastructures. In this paper, we propose a whitelist-based detection system. Network and application-level whitelists are proposed, which are combined to form a novel cross-layer whitelist. Through experiments, we confirm that the proposed whitelists can exactly detect attack packets, which cannot be achieved by existing schemes.

In this paper, a direct/cooperative relay switched single carrier-frequency division multiple access (SC-FDMA) using amplify-and-forward (AF) protocol and spectrum division/adaptive subcarrier allocation (SDASA) is proposed. Using SDASA, the transmit SC signal spectrum is divided into sub-blocks, to each of which a different set of subcarriers (resource block) is adaptively allocated according to the channel conditions of mobile terminal (MT)-relay station (RS) link, RS-base station (BS) link, and MT-BS link. Cooperative relay does not always provide higher capacity than the direct communication. Switching between direct communication and cooperative relay is done depending on the channel conditions of MT-RS, RS-BS, and MT-BS links. We evaluate the achievable channel capacity by the Monte-Carlo numerical computation method. It is shown that the proposed scheme can reduce the transmit power by about 6.0 (2.0) dB compared to the direct communication (the cooperative AF relay) for a 1%-outage capacity of 3.0 bps/Hz.

UWB (Ultra Wideband) radar offers great promise for advanced near field sensors due to its high range resolution. In particular, it is suitable for rescue or resource exploration robots, which need to identify a target in low visibility or acoustically harsh environments. Recently, radar algorithms that actively coordinate multiple scattered components have been developed to enhance the imaging range beyond what can be achieved by synthesizing a single scattered component. Although we previously developed an accurate algorithm for imaging shadow regions with low computational complexity using derivatives of observed ranges for double scattered signals, the algorithm yields inaccurate images under the severe interference situations that occur with complex-shaped or multiple objects or in noisy environments. This is because small range fluctuations arising from interference or random noises can produce non-negligible image degradation owing to inaccuracy in the range derivative calculation. As a solution to this difficulty, this paper proposes a novel imaging algorithm that does not use the range derivatives of doubly scattered signals, and instead extracts a feature of expansive distributions of the observed ranges, using a unique property inherent to the doubly scattering mechanism. Numerical simulation examples of complex-shaped or multiple targets are presented to demonstrate the distinct advantage of the proposed algorithm which creates more accurate images even for complicated objects or in noisy situations.

We propose a compact and high-range resolution 76 GHz millimeter-wave radar system for autonomous unmanned helicopters. The purpose of the radar system is to detect and avoid obstacles that may affect the flight safety. To achieve these objectives, a high range resolution and a long detection range are required for the radar systems with small volume and weight. The radar broadband RF front-end module which employs a simple direct conversion method is proposed. The radar module enables the 6 GHz RF signal transmission as well as the output power of about 8 dBm using commercially available low-cost monolithic microwave integrated circuits. The radar system comprises the broadband RF front-end module, a Ku-band local frequency-modulated continuous wave signal synthesizer, and a very light weight carbon fiber reinforced plastic parabolic reflector antenna. The 5 cm of range resolution is experimentally obtained using the 6 GHz RF signal bandwidth. The results of the power line measurement confirm an about 23 dB signal to noise ratio, which is measured from the reflection of the high-voltage power lines about 150 m ahead. In addition, the results of the radar system on-board test using an unmanned helicopter are evaluated. The real-time radar scope, which is transferred through the wireless connection, confirms the detection of the power lines and the other surrounding objects.

We present a small-area second-order all-digital time-to-digital converter (TDC) with two frequency shift oscillators (FSOs) comprising inverter chains and dynamic flipflops featuring low jitter. The proposed FSOs can maintain their phase states through continuous oscillation, unlike conventional gated ring oscillators (GROs) that are affected by transistor leakage. Our proposed FSOTDC is more robust and is eligible for all-digital TDC architectures in recent leaky processes. Low-jitter dynamic flipflops are adopted as a quantization noise propagator (QNP). A frequency mismatch occurring between the two FSOs can be canceled out using a least mean squares (LMS) filter so that second-order noise shaping is possible. In a standard 65-nm CMOS process, an SNDR of 61 dB is achievable at an input bandwidth of 500 kHz and a sampling rate of 16 MHz, where the respective area and power are 700 µm2 and 281 µW.

This paper presents an adaptive cache architecture for wide-range reliable low-voltage operations. The proposed associativity-reconfigurable cache consists of pairs of cache ways so that it can exploit the recovery feature of the novel 7T/14T SRAM cell. Each pair has two operating modes that can be selected based upon the required voltage level of current operating conditions: normal mode for high performance and dependable mode for reliable low-voltage operations. We can obtain reliable low-voltage operations by application of the dependable mode to weaker pairs that cannot operate reliably at low voltages. Meanwhile leaving stronger pairs in the normal mode, we can minimize performance losses. Our chip measurement results show that the proposed cache can trade off its associativity with the minimum operating voltage. Moreover, it can decrease the minimum operating voltage by 140 mV achieving 67.48% and 26.70% reduction of the power dissipation and energy per instruction. Processor simulation results show that designing the on-chip caches using the proposed scheme results in 2.95% maximum IPC losses, but it can be chosen various performance levels. Area estimation results show that the proposed cache adds area overhead of 1.61% and 5.49% in 32-KB and 256-KB caches, respectively.

The quadtree-based variable block sized prediction makes the biggest contribution for dramatically improved coding efficiency in the new video coding standard named HEVC. However, this technique takes about 75–80% computational complexity of an HEVC encoder. This paper brings forward an adaptive scheme that exploits temporal, spatial and transform-domain features to speed up the original quadtree-based prediction, targeting at high resolution videos. Before encoding starts, analysis on utilization ratio of each coding depth is performed to skip rarely adopted coding depths at frame level. Then, texture complexity (TC) measurement is applied to filter out none-contributable coding blocks for each largest coding unit (LCU). In this step, a dynamic threshold setting approach is proposed to make filtering adaptable to videos and coding parameters. Thirdly, during encoding process, sum of absolute quantized residual coefficient (SAQC) is used as criterion to prune useless coding blocks for both LCUs and 3232 blocks. By using proposed scheme, motion estimation is performed for prediction blocks within a narrowed range. Experiments show that proposed scheme outperforms existing works and speeds up original HEVC by a factor of up to 61.89% and by an average of 33.65% for 4kx2k video sequences. Meanwhile, the peak signal-to-noise ratio (PSNR) degradation and bit increment are trivial.

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.

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 letter proposes a new mechanism that supports adaptive sending control using Real-Time Streaming Protocol (RTSP) and Transmission Control Protocol (TCP) for IPTV service over heterogeneous networks. The proposed mechanism is implemented on a mobile IPTV device and its performance is verified for providing seamless television watching in heterogeneous networks, even when in motion.

The GPS trajectory databases serve as bases for many intelligent applications that need to extract some trajectories for future processing or mining. When doing such tasks, spatio-temporal range queries based methods, which find all sub-trajectories within the given spatial extent and time interval, are commonly used. However, the history trajectory indexes of such methods suffer from two problems. First, temporal and spatial factors are not considered simutaneously, resulting in low performance when processing spatio-temporal queries. Second, the efficiency of indexes is sensitive to query size. The query performance changes dramatically as the query size changed. This paper proposes workload-aware Adaptive OcTree based Trajectory clustering Index (ATTI) aiming at optimizing trajectory storage and index performance. The contributions are three-folds. First, the distribution and time delay of the trajectory storage are introduced into the cost model of spatio-temporal range query; Second, the distribution of spatial division is dynamically adjusted based on GPS update workload; Third, the query workload adaptive mechanism is proposed based on virtual OcTree forest. A wide range of experiments are carried out over Microsoft GeoLife project dataset, and the results show that query delay of ATTI could be about 50% shorter than that of the nested index.

The important issue of an adaptive scheduling scheme is to maximize throughput while providing fair services to all users, especially under strict quality of service requirements. To achieve this goal, we consider the problem of multiuser scheduling under a given fairness constraint. A novel Adaptive Fairness and Throughput Control (AFTC) approach is proposed to maximize the network throughput while attaining a given min-max fairness index. Simulation results reveal that comparing to straightforward methods, the proposed AFTC approach can achieve the desired fairness while maximizing the throughput with short convergence time, and is stable in dynamic scenarios. The trade-off between fairness and throughput can be accurately controlled by adjusting the scheduler's parameters.

Numerous examples in image processing have demonstrated that human visual perception can be exploited to improve processing performance. This paper presents another showcase in which some visual information is employed to guide adaptive block-wise compressive sensing (ABCS) for image data, i.e., a varying CS-sampling rate is applied on different blocks according to the visual contents in each block. To this end, we propose a visual analysis based on the discrete cosine transform (DCT) coefficients of each block reconstructed at the decoder side. The analysis result is sent back to the CS encoder, stage-by-stage via a feedback channel, so that we can decide which blocks should be further CS-sampled and what is the extra sampling rate. In this way, we can perform multiple passes of reconstruction to improve the quality progressively. Simulation results show that our scheme leads to a significant improvement over the existing ones with a fixed sampling rate.

The imaging of humans using radar is promising for surveillance systems. Although conventional radar systems detect the presence or position of intruders, it is difficult to acquire shape and motion details because the resolution is insufficient. This paper presents a high-resolution human imaging algorithm for an ultra-wideband (UWB) Doppler radar. The proposed algorithm estimates three-dimensional human images using interferometry and, using velocity information, rejects false images created by the interference of body parts. Experiments verify that our proposed algorithm achieves adequate pedestrian imaging. In addition, accurate shape and motion parameters are extracted from the estimated images.

Compressive sensing enables quite lower sampling rate compared with Nyquist sampling. As long as the signal is sparsity in some basis, the random sampling with CS can be employed. In order to make CS applied in the practice, the Analog to Information Converter (AIC) should be involved. Based on the Limited Random Sequence (LRS) modulation, the AIC with LRS can be designed with high performance according to the fixed sparsity. However, if the sparsity of the signal varies with time, the original AIC with LRS is not efficient. In this paper, the adaptive AIC which adapts its scheme of LRS according to the variation of the sparsity is proposed and the prototype system is designed. Due to the adaption of the AIC with the scheme of LRS, the sampling rate can be further reduced. The simulation results confirm the performance of the proposed adaptive AIC scheme. The prototype system can successfully fulfil the random sampling and adapt to the variation of sparsity, which verify and consolidate the validity and feasibility for the future implementation of adaptive AIC on chip.

The explosive growth of the usage along with a greater diversification of communication technologies and applications imposes the Internet to manage further scalability and diversity, requiring more adaptive and flexible sharing schemes of network resources. Especially when a number of large-scale distributed applications concurrently share the resource, efficacy of comprehensive usage of network, computation, and storage resources is needed from the viewpoint of information processing performance. Therefore, a reconsideration of the coordination and partitioning of functions between networks (providers) and applications (users) has become a recent research topic. In this paper, we first address the need and discuss the feasibility of adaptive network services by introducing special processing nodes inside the network. Then, a design and an implementation of an advanced relay node platform are presented, by which we can easily prototype and test a variety of advanced in-network processing on Linux and off-the-shelf PCs. A key feature of the proposed platform is that integration between kernel and userland spaces enables to easily and quickly develop various advanced relay processing. Finally, on the top of the advanced relay node platform, we implement and test an adaptive packet compression scheme that we previously proposed. The experimental results show the feasibility of both the developed platform and the proposed adaptive packet compression.

Ultra wideband radar is one of the most promising techniques for non-invasive imaging in a dielectric medium, which is suitable for both medical screening and non-destructive testing applications. A novel imaging method for such an application is proposed in this brief paper, which has been extended from the advanced range points migration method to a multi-static observation model with circular arrays. One notable feature of this method is that it is applicable to either arbitrary dielectric or internal object shapes, and it can also expand the reconstructible image region compared with that obtained using the mono-static model by employing received signals after penetrating various propagation paths in dielectric medium. Numerical results for the investigation of an elliptical object, surrounded by a random dielectric surface, show the remarkable advantages of the proposed method with respect to image expansion.

A method of calibration for GPR responses is introduced in order to extract a target response from GPR data. This calibration procedure eliminates undesirable waveform distortion that is caused by antenna characteristics and multiple scattering effects between the antennas and the ground surface. An application result to measured GPR data shows that undesirable late-time responses caused by the antenna characteristics and multiple scattering effects are removed, and that the target response is clearly reconstructed. This result demonstrates that the waveform calibration of GPR data is significant and essential for reliable target identification.

We investigate the visibility of scrolling text presented nearby a dynamically moving image. In two experiments, we evaluate the subjective speed and readability of scrolled fake addresses presented immediately above a moving grating pattern that covers a large part of the visual field. The drift speed and direction of the grating were controlled to reveal the visibility of the text. The results show that the scrolling addresses exhibited slower subjective speed and better readability when the grating moved in the same direction as the scrolling addresses. On the contrary, faster subjective speed and worse readability of the scrolling addresses were raised by the grating moving in the opposite direction. The strength of these effects was dependent on the speed difference between the scrolling addresses and the grating. These results suggest that the visibility of the scrolling text, assessed in terms of subjective speed and readability, strongly depends on nearby moving images.