Link prediction in social networks, such as friendship networks and coauthorship networks, has recently attracted a great deal of attention. There have been numerous attempts to address the problem of link prediction through diverse approaches. In the present paper, we focus on the temporal behavior of the link strength, particularly the relationship between the time stamps of interactions or links and the temporal behavior of link strength and how link strength affects future link evolution. Most previous studies have not sufficiently discussed either the impact of time stamps of the interactions or time stamps of the links on link evolution. The gap between the current time and the time stamps of the interactions or links is also important to link evolution. In the present paper, we introduce a new time-aware feature, referred to as time score, that captures the important aspects of time stamps of interactions and the temporality of the link strengths. We also analyze the effectiveness of time score with different parameter settings for different network data sets. The results of the analysis revealed that the time score was sensitive to different networks and different time measures. We applied time score to two social network data sets, namely, Facebook friendship network data set and a coauthorship network data set. The results revealed a significant improvement in predicting future links.

This paper proposes an efficient list extension algorithm for soft-output multiple-input-multiple-output (soft-MIMO) detection. This algorithm extends the list of candidate vectors based on the vector selected by initial detection, in order to solve the empty-set problem, while reducing the number of additional vectors. The additional vectors are obtained from multiple detection orders, from which high-quality soft-output can be generated. Furthermore, a method to reduce the complexity of the determination of the multiple detection orders is described. From simulation results for a 44 system with 16- and 64-quadrature amplitude modulations (QAM) and rate 1/2 and 5/6 duo-binary convolutional turbo code (CTC), the soft-MIMO detection to which the proposed list extension was applied showed a performance degradation of less than 0.5 dB at bit error rate (BER) of 10-5, compared to that of the soft-output maximum-likelihood detection (soft-MLD) for all code rate and modulation pairs, while the complexity of the proposed list extension was approximately 38% and 17% of that of an existing algorithm with similar performance in a 44 system using 16- and 64-QAM, respectively.

Railway inspection is important in railway maintenance. There are several tasks in railway inspection, e.g., defect detection and bolt detection. For those inspection tasks, the detection of rail surface is a fundamental and key issue. In order to detect rail defects and missing bolts, one must know the exact location of the rail surface. To deal with this problem, we propose an efficient Rail Surface Detection (RSD) algorithm that combines boundary and region information in a uniform formulation. Moreover, we reevaluate the rail location by introducing the top down information–bolt location prior. The experimental results show that the proposed algorithm can detect the rail surface efficiently.

We quantitatively evaluate how sampling and spatio/temporal granularity in traffic monitoring affect the detectability of anomalous traffic. Those parameters also affect the monitoring burden, so network operators face a trade-off between the monitoring burden and detectability and need to know which are the optimal paramter values. We derive equations to calculate the false positive ratio and false negative ratio for given values of the sampling rate, granularity, statistics of normal traffic, and volume of anomalies to be detected. Specifically, assuming that the normal traffic has a Gaussian distribution, which is parameterized by its mean and standard deviation, we analyze how sampling and monitoring granularity change these distribution parameters. This analysis is based on observation of the backbone traffic, which exhibits spatially uncorrelated and temporally long-range dependence. Then we derive the equations for detectability. With those equations, we can answer the practical questions that arise in actual network operations: what sampling rate to set to find the given volume of anomaly, or, if the sampling is too high for actual operation, what granularity is optimal to find the anomaly for a given lower limit of sampling rate.

Cognitive radio (CR) in spectrum sharing mode allows secondary user (SU) to share the same spectrum simultaneously with primary user (PU), as long as the former guarantees no harmful interference is caused to the latter. This letter proposes a new type of constraint to protect the PU systems that are carrying delay-sensitive applications, namely the PU effective capacity loss constraint, which sets an upper bound on the maximum effective capacity loss of the PU due to the SU transmission. In addition, the PU effective capacity loss constraint is approximately transformed to the interference temperature (power) constraint, to make it easier to be implemented. As an example, we obtain a closed form expression of the SU effective capacity under the approximated peak interference power constraint and the results of simulations validate the proposed PU protection criterion.

A novel Template Updating system for fingerprint verification systems used in mobile applications is introduced in the paper. Based on the proposed method, the system performance is improved much more than the original one. Not only the FRR (False Reject Rate) but also the small overlap problem caused by the very narrow sensor on the mobile phone are solved. Based on the template updating system, templates are replaced with matched inputs towards a target structure which can expand the coverage of templates with large displacement and rotation. By using the test database, the system performance shows the FRR can be reduced by 79% in comparison with the one without template updating procedure. This system was adopted in practical mobile phones in the commercial market in 2009.

The continuous advances in sensing and positioning technologies have resulted in a dramatic increase in popularity of Location-Based Services (LBS). Nevertheless, the LBS can lead to user privacy breach due to sharing location information with potentially malicious services. A high degree of location privacy preservation for LBS is extremely required. In this paper, a clustering K-anonymity scheme for location privacy preservation (namely CK) is proposed. The CK scheme does not rely on a trusted third party to anonymize the location information of users. In CK scheme, the whole area that all the users reside is divided into clusters recursively in order to get cloaked area. The exact location information of the user is replaced by the cloaked spatial temporal boundary (STB) including K users. The user can adjust the resolution of location information with spatial or temporal constraints to meet his personalized privacy requirement. The experimental results show that CK can provide stringent privacy guarantees, strong robustness and high QoS (Quality of Service).

The increase in the advanced location based services such as traffic coordination and management necessitates the need for advanced models tracking the positions of Moving Objects (MOs) like vehicles. Due to computer processing limitations, it is impossible for MOs to continuously update their locations. This results in the uncertainty nature of a MO's location between any two reported positions. Efficiently managing and quantifying the uncertainty regions of MOs are needed in order to support different types of queries and to improve query response time. This challenging problem of modeling uncertainty regions associated with MO was recently addressed by researchers and resulted in models that ranged from linear which require few properties of MOs as input to the models, to non-linear that are able to more accurately represent uncertainty regions by considering higher degree input. This paper summarizes and discusses approaches in modeling uncertainty regions associated with MOs. It further illustrates the need for appropriate approximations especially in the case of non-linear models as the uncertainty regions become rather irregularly shaped and difficult to manage. Finally, we demonstrate through several experimental sets the advantage of non-linear models over linear models when the uncertainty regions of MOs are approximated by two different approximations; the Minimum Bounding Box (MBB) and the Tilted Minimum Bounding Box (TMBB).

In off-line analysis, the demand for high precision signal processing has introduced a new method called Empirical Mode Decomposition (EMD), which is used for analyzing a complex set of data. Unfortunately, EMD is highly compute-intensive. In this paper, we show parallel implementation of Empirical Mode Decomposition on a GPU. We propose the use of “partial+total” switching method to increase performance while keeping the precision. We also focused on reducing the computation complexity in the above method from O(N) on a single CPU to O(N/P log (N)) on a GPU. Evaluation results show our single GPU implementation using Tesla C2050 (Fermi architecture) achieves a 29.9x speedup partially, and a 11.8x speedup totally when compared to a single Intel dual core CPU.

Due to the increased power density and lower thermal conductivity, 3D ICs are faced with heat dissipation and temperature problem seriously. TSV (Through-Silicon-Via) has been shown as an effective way to help heat removal, but they introduce several issues related with cost and reliability as well. Previous researches of TSV planning didn't pay much attention to the impact of leakage power, which will bring in error on estimation of temperature, TSV number and also critical path delay. The leakage-temperature-delay dependence can potentially negate the performance improvement of 3D designs. In this paper, we analyze the impact of leakage power on TSV planning and integrate leakage-temperature-delay dependence into thermal via planning of 3D ICs. A weighted via insertion approach, considering the influence on both module delay and wire delay, is proposed to achieve the best balance among temperature, via number and performance. Experiment results show that, with leakage power and resource constraint considered, temperature and the required via number can be quite different, and the weighted TSV insertion approach with iterative process can obtain the trade-off between different factors including thermal, power consumption, via number and performance.

An on-chip temperature compensation active bias circuit having tunable temperature slope has been proposed, and its application to an X-band GaAs FET monolithic microwave integrated circuit (MMIC) power amplifier (PA) is described. The proposed bias circuit can adjust the temperature slope of gate voltage according to the bias condition of the PA, and also realizes the higher temperature slope of the gate voltage by employing the diode and the FET which operates at near threshold voltage (Vt) in the bias circuit. As a result, the gain of PAs operated at any bias conditions is kept almost constant against temperature by applying the proposed bias circuit. Moreover, the proposed bias circuit can be integrated in the same chip with the MMIC PA since it does not need off-chip components, and operates with only negative voltage source. The fabricated results of the on-chip temperature compensation active bias circuit shows that the temperature slope of the gate voltage varies from 2.1 to 6.3 mV/, which is enough to compensate the gain of not only class-B PA but also class-A PA. The gain deviation of the developed GaAs FET MMIC PA with the proposed bias circuit has been reduced from 3.3 dB to 0.6 dB in the temperature range of 100.

Proving the security of cancelable biometrics and other template protection techniques is a key prerequisite for the widespread deployment of biometric technologies. BioEncoding is a cancelable biometrics scheme that has been proposed recently to protect biometric templates represented as binary strings like iris codes. Unlike other template protection schemes, BioEncoding does not require user-specific keys or tokens. Moreover, it satisfies the requirements of untraceable biometrics without sacrificing the matching accuracy. However, the security of BioEncoding against smart attacks, such as correlation and optimization-based attacks, has to be proved before recommending it for practical deployment. In this paper, the security of BioEncopding, in terms of both non-invertibility and privacy protection, is analyzed. First, resistance of protected templates generated using BioEncoding against brute-force search attacks is revisited rigorously. Then, vulnerabilities of BioEncoding with respect to correlation attacks and optimization based attacks are identified and explained. Furthermore, an important modification to the BioEncoding algorithm is proposed to enhance its security against correlation attacks. The effect of integrating this modification into BioEncoding is validated and its impact on the matching accuracy is investigated empirically using CASIA-IrisV3-Interval dataset. Experimental results confirm the efficacy of the proposed modification and show that it has no negative impact on the matching accuracy.

In this paper, a preemptive priority queueing model is developed to derive the system dwelling time of secondary calls in a cognitive radio system in which a primary call's reoccupation of the channel is modeled as a preemptive event that forces a secondary call to attempt a spectrum handover. The suspension of secondary call service which may happen when the immediate spectrum handover fails, is included in our computation of the system dwelling time. The results are helpful in evaluating cognitive radio systems in terms of service delay and in determining system design parameters such as required buffer size and system capacity.

A stereo video coding scheme which is compatible with monoview-processor is presented in this paper. At the same time, this paper proposes an adaptive prediction structure which can make different prediction modes to be applied to different groups of picture (GOPs) according to temporal correlations and interview correlations to improve the coding efficiency. Moreover, the most advanced video coding standard H.264 is used conveniently for maximize the coding efficiency in this paper. Finally, the effectiveness of the proposed scheme is verified by extensive experimental results.

We develop an effective algorithm, based on the filtered backprojection (FBP) approach, for the imaging of vegetation. Under the FBP scheme, the reconstruction amounts at a non-trivial Fourier inversion, since the data are Fourier samples arranged on a non-Cartesian grid. The computational issue is efficiently tackled by Non-Uniform Fast Fourier Transforms (NUFFTs), whose complexity grows asymptotically as that of a standard FFT. Furthermore, significant speed-ups, as compared to fast CPU implementations, are obtained by a parallel versions of the NUFFT algorithm, purposely designed to be run on Graphic Processing Units (GPUs) by using the CUDA language. The performance of the parallel algorithm has been assessed in comparison to a CPU-multicore accelerated, Matlab implementation of the same routine, to other CPU-multicore accelerated implementations based on standard FFT and employing linear, cubic, spline and sinc interpolations and to a different, parallel algorithm exploiting a parallel linear interpolation stage. The proposed approach has resulted the most computationally convenient. Furthermore, an indoor, polarimetric experimental setup is developed, capable to isolate and introduce, one at a time, different non-idealities of a real acquisition, as the sources (wind, rain) of temporal decorrelation. Experimental far-field polarimetric measurements on a thuja plicata (western redcedar) tree point out the performance of the set up algorithm, its robustness against data truncation and temporal decorrelation as well as the possibility of discriminating scatterers with different features within the investigated scene.

We propose a subthreshold Static Random Access Memory (SRAM) circuit architecture with improved write ability. Even though the circuits can achieve ultra-low power dissipation in subthreshold digital circuits, the performance is significantly degraded with threshold voltage variations due to the fabrication process and temperature. Because the write operation of SRAM is prone to failure due to the unbalance of threshold voltages between the nMOSFET and pMOSFET, stable operation cannot be ensured. To achieve robust write operation of SRAM, we developed a compensation technique by using an adaptive voltage scaling technique that uses an on-chip threshold voltage monitoring circuit. The monitoring circuit detects the threshold voltage of a MOSFET with the on-chip circuit configuration. By using the monitoring voltage as a supply voltage for SRAM cells, write operation can be compensated without degrading cell stability. Monte Carlo simulations demonstrated that the proposed SRAM architecture exhibits a smaller write operation failure rate and write time variation than a conventional 6T SRAM.

This paper proposes an area efficient, low power, fractional CMOS bandgap reference (BGR) utilizing switched-current and current-memory techniques. The proposed circuit uses only one parasitic bipolar transistor and built-in current source to generate reference voltage. Therefore significant area and power reduction is achieved, and bipolar transistor device mismatch is eliminated. In addition, output reference voltage can be set to almost any value. The proposed circuit is designed and simulated in 0.18 µm CMOS process, and simulation results are presented. With a 1.6 V supply, the reference produces an output of about 628.5 mV, and simulated results show that the temperature coefficient of output is less than 13.8 ppm/ in the temperature range from 0 to 100. The average current consumption is about 8.5 µA in the above temperature range. The core circuit, including current source, opamp, current mirrors and switched capacitor filters, occupies less than 0.0064 mm2 (80 µm×80 µm).

Resistive switching of metal-insulator-metal (MIM), consisting of a metal-organic chemical vapour deposition (MOCVD) TiO2 layer sandwiched between Pt electrodes, has been measured systematically before and after thermal annealing in different ambiences. With H2 annealing at 400, the current level in the high-resistive state (HRS) significantly decreased while little change in the low-resistive state (LRS) was observed. As a result, the switching ratio over 7 orders of magnitude at the current level was obtained. From the analysis of current-voltage (I-V) characteristics in HRS and LRS, we found that the LRS was characterized with an ohmic conduction, while in the HRS after H2 annealing, charge trapping became significant as a result of a significant decrease in the current level. In a separate experiment, a partial reduction in TiO2 was detected using high-resolution X-ray photoelectron spectroscopy (XPS) after resistant-state switching from HRS to LRS by using a Hg probe as a top electrode, which is associated with filament formation.

This paper presents a resistor-compensation technique for a CMOS bandgap and current reference, which utilizes various high positive temperature coefficient (TC) resistors, a two-stage operational transconductance amplifier (OTA) and a simplified start-up circuit in the 0.35-µm CMOS process. In the proposed bandgap and current reference, numerous compensated resistors, which have a high positive temperature coefficient (TC), are added to the parasitic n-p-n and p-n-p bipolar junction transistor devices, to generate a temperature-independent voltage reference and current reference. The measurements verify a current reference of 735.6 nA, the voltage reference of 888.1 mV, and the power consumption of 91.28 µW at a supply voltage of 3.3 V. The voltage TC is 49 ppm/ in the temperature range from 0 to 100 and 12.8 ppm/ from 30 to 100. The current TC is 119.2 ppm/ at temperatures of 0 to 100. Measurement results also demonstrate a stable voltage reference at high temperature (> 30), and a constant current reference at low temperature (< 70).

A new kind of 3D power divider based on a half-mode substrate integrated circular cavity (HSICC) is proposed. This novel power divider can reduce the size of a power divider based on normal substrate integrated circular cavity (SICC) by nearly a half. To verify the validity of the design method, a two-way X-band HSICC power divider using low temperature co-fired ceramic (LTCC) technology is designed, fabricated and measured.