Link prediction is the task of inferring the existence or absence of certain relationships among data objects such as identity, interaction, and collaboration. Link prediction is found in various applications in the fields of information integration, recommender systems, bioinformatics, and social network analysis. The increasing interest in dynamically changing networks has led to growing interest in a more general link prediction problem called temporal link prediction in the data mining and machine learning communities. However, only links among nodes at the same time point are considered in temporal link prediction. We propose a new link prediction problem called cross-temporal link prediction in which the links among nodes at different time points are inferred. A typical example of cross-temporal link prediction is cross-temporal entity resolution to determine the identity of real entities represented by data objects observed in different time periods. In dynamic environments, the features of data change over time, making it difficult to identify cross-temporal links by directly comparing observed data. Other examples of cross-temporal links are asynchronous communications in social networks such as Facebook and Twitter, where a message is posted in reply to a previous message. We adopt a dimension reduction approach to cross-temporal link prediction; that is, data objects in different time frames are mapped into a common low-dimensional latent feature space, and the links are identified on the basis of the distance between the data objects. The proposed method uses different low-dimensional feature projections in different time frames, enabling it to adapt to changes in the latent features over time. Using multi-task learning, it jointly learns a set of feature projection matrices from the training data, given the assumption of temporal smoothness of the projections. The optimal solutions are obtained by solving a single generalized eigenvalue problem. Experiments using a real-world set of bibliographic data for cross-temporal entity resolution and a real-world set of emails for unobserved asynchronous communication inference showed that introducing time-dependent feature projections improved the accuracy of link prediction.

In recent years, there has been an increasing demand with regard to available elemental services provided by independent firms for compositing new services. Currently, however, whenever it is difficult to maintain the required level of quality of a new composite web service, assignment of the new computer's resources as provisioning at the data center is not always effective, especially in the area of performance for composite web service providers. Thus, a new approach might be required. This paper presents a new control method aiming to maintain the performance requirements for composite web services. There are three aspects of our method that are applied: first of all, the theory of constraints (TOC) proposed by E.M. Goldratt ; secondly, an evaluation process in the non-linear feed forward controlling method: and finally multiple trials in applying policies with verification. In particular, we will discuss the architectural and theoretical aspects of the method in detail, and will show the insufficiency of combining the feedback controlling approach with TOC as a result of our evaluation.

This paper proposes a third-order low-distortion delta-sigma modulator (DSM). The third-order noise shaping is achieved by a single opamp (excluding the quantizer). In the proposed DSM structure, the timing limitation on the quantizer and dynamic element matching (DEM) logic in a conventional low-distortion structure can be relaxed from a non-overlapping interval to half of the clock period. A cyclic analog-to-digital converter with a loading-free technique is utilized as a quantizer, which shares an opamp with the active adder. The signal transfer function (STF) is preserved as unity, which means that the integrators process only the quantization noise component. As a result, the opamp used for the integrators has lower requirements, as low-distortion DSMs, on slew rate, output swing, and power consumption. The proposed third-order DSM with a 4-bit cyclic-type quantizer is implemented in a 90-nm CMOS process. Under a sampling rate of 80 MHz and oversampling ratio of 16, simulation results show that an 81.97-dB signal-to-noise and distortion ratio and an 80-dB dynamic range are achieved with 4.17-mW total power consumption. The resulting figure of merit (FOM) is 81.5 fJ/conversion-step.

In this study, we propose a cooperative sensing with distributed pre-detection for gathering sensing information on shared primary system. We have proposed a system that gathers multiple sensing information by using the orthogonal narrowband signal; the system is called the orthogonal frequency-based sensing information gathering (OF-SIG) method. By using this method, sensing information from multiple secondary nodes can be gathered from the surrounding secondary nodes simultaneously by using the orthogonal narrowband signals. The advantage of this method is that the interference from each node is small because a narrowband tone signal is transmitted from each node. Therefore, if appropriate power and transmission control are applied at the surrounding nodes, the sensing information can be gathered in the same spectrum as the primary system. To avoid interference with the primary receiver, we propose a cooperative sensing with distributed pre-detection for gathering sensing information in each node by limiting sensing node power. In the proposed method, the number of sensing information transmitting nodes depends on the pre-detection ability of the individual sensing at each node. Then the secondary node can increase the transmit power by improving the sensing detection ability, and the secondary node can gather the sensing information from the surrounding secondary nodes which are located more far by redesign the transmit power of the secondary nodes. Here, we design the secondary transmit power based on OF-SIG while considering the aggregated interference from multiple sensing nodes and individual sensing ability. Finally we confirm the performance of the cooperative sensing of the proposed method through computer simulation.

When the Akebono (EXOS-D) satellite passed through the plasmasphere, a series of lightning whistlers was observed by its analog wideband receiver (WBA). Recently, we developed an intelligent algorithm to detect lightning whistlers from WBA data. In this study, we analyzed two typical events representing the clear dispersion characteristics of lightning whistlers along the trajectory of Akebono. The event on March 20, 1991 was observed at latitudes ranging from 47.83 (47,83N) to -11.09 (11.09S) and altitudes between ∼2232 and ∼7537 km. The other event on July 12, 1989 was observed at latitudes from 34.94 (34.94N) and -41.89 (41.89S) and altitudes ∼1420–∼7911 km. These events show systematic trends; hence, we can easily determine whether the wave packets of lightning whistlers originated from lightning strikes in the northern or the southern hemispheres. Finally, we approximated the path lengths of these lightning whistlers from the source to the observation points along the Akebono trajectory. In the calculations, we assumed the dipole model as a geomagnetic field and two types of simple electron density profiles in which the electron density is inversely proportional to the cube of the geocentric distance. By scrutinizing the dipole model we propose some models of dispersion characteristic that proportional to the electron density. It was demonstrated that the dispersion D theoretically agrees with observed dispersion trend. While our current estimation is simple, it shows that the difference between our estimation and observation data is mainly due to the electron density profile. Furthermore, the dispersion analysis of lightning whistlers is a useful technique for reconstructing the electron density profile in the Earth's plasmasphere.

Fast and accurate estimation of missing relations, e.g., similarity, distance and kernel, among objects is now one of the most important techniques required by major data mining tasks, because the missing information of the relations is needed in many applications such as economics, psychology, and social network communities. Though some approaches have been proposed in the last several years, the practical balance between their required computation amount and obtained accuracy are insufficient for some class of the relation estimation. The objective of this paper is to formalize a problem to quickly and efficiently estimate missing relations among objects from the other known relations among the objects and to propose techniques called “PSD Estimation” and “Row Reduction” for the estimation problem. This technique uses a characteristic of the relations named “Positive Semi-Definiteness (PSD)” and a special assumption for known relations in a matrix. The superior performance of our approach in both efficiency and accuracy is demonstrated through an evaluation based on artificial and real-world data sets.

This paper proposes a low-complexity concatenated (LCC) soft-in soft-out (SISO) detector for spreading OFDM systems. The LCC SISO detector uses the turbo principle to compute the extrinsic information of the optimal maximum a priori probability (MAP) SISO detector with extremely low complexity. To develop the LCC SISO detector, we first partition the spreading matrix into some concatenated sparse matrices separated by interleavers. Then, we use the turbo principle to concatenate some SISO detectors, which are separated by de-interleavers or interleavers. Each SISO detector computes the soft information for each sparse matrix. By exchanging the soft information between the SISO detectors, we find the extrinsic information of the MAP SISO detector with extremely low complexity. Simulation results show that using the LCC SISO detector produces a near-optimal performance for both uncoded and coded spreading OFDM systems. In addition, by using the LCC SISO detector, the spreading OFDM system significantly improves the BER of the conventional OFDM system.

We observe that the state-of-the-art power-saving mechanisms (PSM) for IEEE 802.16e is neither optimal in terms of delay nor in terms of energy consumption. We propose a new PSM which achieves the optimality in terms of the average buffering delay without increasing energy consumption. In order to do so, we derive a formula which relates the average buffering delay to sleep intervals. Simulation results show that our scheme surpasses the BTE algorithm (used by the current IEEE 802.16e Mobile Stations) by 56.75–76% and the PSID algorithm by 8.52–24.39% in terms of the delay-energy consumption product.

Blind source separation (BSS) techniques are required for various signal decomposing issues. Independent component analysis (ICA), assuming only a statistical independence among stochastic source signals, is one of the most useful BSS tools because it does not need a priori information on each source. However, there are many requirements for decomposing multiple deterministic signals such as complex sinusoidal signals with different frequencies. These requirements may include pulse compression or clutter rejection. It has been theoretically shown that an ICA algorithm based on maximizing non-Gaussianity successfully decomposes such deterministic signals. However, this ICA algorithm does not maintain a sufficient separation performance when the frequency difference of the sinusoidal waves becomes less than a nominal frequency resolution. To solve this problem, this paper proposes a super-resolution algorithm for complex sinusoidal signals by extending the maximum likelihood ICA, where the probability density function (PDF) of a complex sinusoidal signal is exploited as a priori knowledge, in which the PDF of the signal amplitude is approximated as a Gaussian distribution with an extremely small standard deviation. Furthermore, we introduce an optimization process for this standard deviation to avoid divergence in updating the reconstruction matrix. Numerical simulations verify that our proposed algorithm remarkably enhances the separation performance compared to the conventional one, and accomplishes a super-resolution separation even in noisy situations.

In this paper, we propose a hardware architecture of high-speed sorted QR decomposition for 44 MIMO wireless communication systems. QR decomposition (QRD) is commonly used in many MIMO detection algorithms. In particular, sorted QR decomposition (SQRD) is the advanced algorithm to improve MIMO detection performance. We design an SQRD hardware architecture by using a modified Gram-Schmidt algorithm with pipelining and recursive processing. In addition, we propose an extended architecture which can decompose an augmented channel matrix for MMSE MIMO detection. These architecture can be applied in high-throughput MIMO-OFDM system such as IEEE802.11n which supports data throughput of up to 600 Mbps. We implement the proposed SQRD architecture and the proposed MMSE-SQRD architecture with 179k and 334k gates in 90 nm CMOS technology. These proposed design can achieve a high performance of up to 40.8 and 50.0 million 44 SQRD operations per second with the maximum operating frequency of 245 and 300 MHz.

Limited Random Sequence (LRS) is quite important for Analog-to-Information Converter (AIC) because it determines the random sampling scheme and the resultant performance. LRS is established with the elements of “0” and “1”. The “1” appears randomly in the segment of the sequence, so that the production of the original signal and LRS can be considered as the approximation of the random sampling of the original signal. The random sampling result can perfectly recover the signal with Compressive Sensing (CS) algorithm. In this paper, a high order LRS is proposed for the AIC design in Distributed Compressive Sensing (DCS), which has the following three typical features: 1) The high order LRS has the elements of integer which can indicate the index number of the sensor in DCS. 2) High order LRS can adapt to the sparsity variation of the original signal detected by each sensor. 3) Employing the AIC with high order LRS, the DCS algorithm can recover the signal with very low sampling rate, usually above 2 orders less than the traditional distributed sensors. In the paper, the scheme and the construction algorithm of high order LRS are proposed. The performance is evaluated with the application studies of the distributed sensor network and the camera picture correspondingly.

This paper proposes a downlink multi-user transmission scheme for the amplify-and-forward(AF)-based multi-relay cellular network, in which Tomlinson-Harashima precoding(TH precoding) and interference alignment(IA) are jointly applied. The whole process of transmission is divided into two phases: TH precoding is first performed at base-station(BS) to support the multiplexing of data streams transmitted to both mobile-stations(MS) and relay-stations(RS), and then IA is performed at both BS and RSs to achieve the interference-free communication. During the whole process, neither data exchange nor strict synchronization is required among BS and RSs thus reducing the cooperative complexity as well as improving the system performance. Theoretical analysis is provided with respect to the channel capacity of different types of users, resulting the upper-bounds of channel capacity. Our analysis and simulation results show that the joint applications of TH precoding and IA outperforms other schemes in the presented multi-relay cellular network.

A scheme that modulates the training sequence is proposed to support two-layer data streams in the time domain synchronous orthogonal frequency division multiplex (TDS-OFDM) systems. A theoretical analysis and computer simulation show that the proposed scheme works well and that the two layer data streams are compatible with each other.

We apply the Hadamard equivalence to all the binary matrices of the size mn and study various properties of this equivalence relation and its classes. We propose to use HR-minimal as a representative of each equivalence class, and count and/or estimate the number of HR-minimals of size mn. Some properties and constructions of HR-minimals are investigated. Especially, we figure that the weight on an HR-minimal's second row plays an important role, and introduce the concept of Quasi-Hadamard matrices (QH matrices). We show that the row vectors of mn QH matrices form a set of m binary vectors of length n whose maximum pairwise absolute correlation is minimized over all such sets. Some properties, existence, and constructions of Quasi-orthogonal sequences are also discussed. We also give a relation of these with cyclic difference sets. We report lots of exhaustive search results and open problems, one of which is equivalent to the Hadamard conjecture.

A laser irradiation experiment for photocurrent induced failure investigations was described. In order to focus a laser beam on a desired transistor, novel test circuit structures using selectively metal-covered transistors were proposed. Photocurrent induced upset failures were successfully observed in fabricated CMOS SRAM test cells. Results were discussed with SPICE simulations.

Constructing APN or 4-differentially uniform permutations achieving all the necessary criteria is an open problem, and the research on it progresses slowly. In ACISP 2011, Carlet put forth an idea for constructing differentially uniform permutations using extension fields, which was illustrated with a construction of a 4-differentially uniform (n,n)-permutation. The permutation has optimum algebraic degree and very good nonlinearity. However, it was proved to be a permutation only for n odd. In this note, we investigate further the construction of differentially uniform permutations using extension fields, and construct a 4-differentially uniform (n,n)-permutation for any n. These permutations also have optimum algebraic degree and very good nonlinearity. Moreover, we consider a more general type of construction, and illustrate it with an example of a 4-differentially uniform (n,n)-permutation with good cryptographic properties.

Linear complexity profile and correlation measure of order k are important pseudorandomness measures for sequences used in cryptography. We study both measures for a class of binary sequences called Legendre-Sidelnikov sequences. The proofs involve character sums.

In time-varying frequency selective channels, to obtain high-rate joint time-frequency diversity, linear dispersion coded orthogonal frequency division multiplexing (LDC-OFDM), has recently been proposed. Compared with OFDM systems, single-carrier systems may retain the advantages of lower PAPR and lower sensitivity to carrier frequency offset (CFO) effects, which motivates this paper to investigate how to achieve joint frequency and time diversity for high-rate single-carrier block transmission systems. Two systems are proposed: linear dispersion coded cyclic-prefix single-carrier modulation (LDC-CP-SCM) and linear dispersion coded zero-padded single-carrier modulation (LDC-ZP-SCM) across either multiple CP-SCM or ZP-SCM blocks, respectively. LDC-SCM may use a layered two-stage LDC decoding with lower complexity. This paper analyzes the diversity properties of LDC-CP-SCM, and provides a sufficient condition for LDC-CP-SCM to maximize all available joint frequency and time diversity gain and coding gain. This paper shows that LDC-ZP-SCM may be effectively equipped with low-complexity minimum mean-squared error (MMSE) equalizers. A lower complexity scheme, linear transformation coded SCM (LTC-SCM), is also proposed with good diversity performance.

A numerical model of multi-layered organic light emitting diode (OLED) is presented in this paper. The current density-voltage (J-V) model for OLED was performed by using the injection-limited current and bulk-limited current. The mobility equation was based on the field dependent model, so called “Poole-Frenkel mobility model.” The accuracy of this simulation was represented by comparing to the experimental results with a variable of EML thickness of multi-layered OLED device. There are two hetero-junction models which should be dealt with in the simulation. The Langevin recombination rate of electron and hole is also calculated through the device simulation.

With the development of Global Navigation Satellite System (GNSS), the amount of related research is growing rapidly in China. A lot of accomplishments have been achieved in all branches of the satellite navigation field, especially motivated by the BeiDou Program. In this paper, the current status, technologies and developments in satellite positioning and navigation in China are introduced. Firstly, an overview and update of the BeiDou Program is presented, known as the three-step development strategy for different services. Then signal design for the BeiDou system is discussed, including the generation of pseudo-random noise (PRN) codes for currently available signal B1, and the investigation of a new signal modulation scheme for interoperability at open frequency B1C. The B1C signal should comply to Multiplexed Binary Offset Carrier (MBOC) constrains, and a modulation called Quadrature Multiplexed BOC (QMBOC) is presented, which is equivalent to time-multiplexed BOC (TMBOC) for GPS and composite BOC (CBOC) for Galileo, while overcomes the drawback of CBOC. Besides, the inter and intra system compatibility is discussed, based on the effective C/N0 proposed by International Telecommunication Union (ITU). After that, receiver technologies in challenging environments are introduced, such as weak signal acquisition and assisted GNSS (A-GNSS). Moreover, a method of ambiguity mitigation for adaptive digital beam forming (ADBF) in large spacing antenna arrays is proposed, by which interference suppression is available. Furthermore, cutting edge technologies are brought in, including seamless navigation for indoor and outdoor, and collaborative navigation. After all, GNSS applications in China for industry and daily life are shown, as well as the market prospection.