In this paper, we propose SimCS (similarity based on contribution scores) to compute the similarity of scientific papers. For similarity computation, we exploit a notion of a contribution score that indicates how much a paper contributes to another paper citing it. Also, we consider the author dominance of papers in computing contribution scores. We perform extensive experiments with a real-world dataset to show the superiority of SimCS. In comparison with SimCC, the-state-of-the-art method, SimCS not only requires no extra parameter tuning but also shows higher accuracy in similarity computation.

The two-dimensional (2D) interference is one of the major impairments in bit-patterned media recording (BPMR) systems due to small bit and track pitches, especially at high recording densities. To alleviate this problem, we introduced a rate-4/5 constructive inter-track interference (CITI) coding scheme to prevent the destructive data patterns to be written onto a magnetic medium for an uncoded BPMR system, i.e., without error-correction codes. Because the CITI code produces only the hard decision, it cannot be employed in a coded BPMR system that uses a low-density parity-check (LDPC) code. To utilize it in an iterative decoding scheme, we propose a soft CITI coding scheme based on the log-likelihood ratio algebra implementation in Boolean logic mappings in order that the soft CITI coding scheme together with a modified 2D soft-output Viterbi algorithm (SOVA) detector and a LDPC decoder will jointly perform iterative decoding. Simulation results show that the proposed scheme provides a significant performance improvement, in particular when an areal density (AD) is high and/or the position jitter is large. Specifically, at a bit-error rate of 10-4 and no position jitter, the proposed system can provide approximately 1.8 and 3.5 dB gain over the conventional coded system without using the CITI code at the ADs of 2.5 and 3.0 Tera-bit per square inch (Tb/in2), respectively.

Conventional localization techniques such as triangulation and multilateration are not reliable in non-line-of-sight (NLOS) environments such as dense urban areas. Although fingerprint-based localization techniques have been proposed to solve this problem, we may face difficulties because we do not know the parameters of the illegal radio when creating the fingerprint database. This paper proposes a novel technique to localize illegal radios in an urban environment by interpolating the channel impulse responses stored as fingerprints in a database. The proposed interpolation technique consists of interpolation in the bandwidth (delay), frequency and spatial domains. A localization algorithm that minimizes the squared error criterion is employed in this paper, and the proposed technique is evaluated through Monte Carlo simulations using location fingerprints obtained from ray-tracing simulations. Results show that utilizing an interpolated fingerprint database is advantageous in such scenarios.

An incremental relaying protocol is a promising scheme for preventing the inefficient use of resources in half-duplex cooperative relay networks. In particular, the incremental selection amplify-and-forward (ISAF) relaying scheme is a well-designed protocol under the condition that the source-to-destination (SD) link is static during the two transmission phases. However, from a practical viewpoint, the SD link is not static but varies with time, and thus the ISAF relaying scheme may not work well in the field. In this work, we first show that the outage performance of the ISAF relaying scheme may decrease when the SD link is not static during the two transmission phases. We then propose a modified version of the ISAF relaying scheme which overcomes such a limitation of the ISAF relaying scheme under time-varying environments. Finally, numerical and simulation results are provided to support our findings.

Recently in the mobile graphic industry, ultra-realistic visual qualities with 60fps and limited power budget for GPU have been required. For graphics-heavy applications that run at 30 fps, we easily observed very noticeable flickering artifacts. Further, the workload imposed by high resolutions at high frame rates directly decreases the battery life. Unlike the recent frame rate up sampling algorithms which remedy the flickering but cause inevitable significant overheads to reconstruct intermediate frames, we propose a dynamic rendering quality scaling (DRQS) that includes dynamic rendering based on resolution changes and quality scaling to increase the frame rate with negligible overhead using a transform matrix. Further DRQS reduces the workload up to 32% without human visual-perceptual changes for graphics-light applications.

The Energy-aware Multi-mode Accelerator eXtension [24],[25] (EMAX) is equipped with distributed single-port local memories and ring-formed interconnections. The accelerator is designed to achieve extremely high throughput for scientific computations, big data, and image processing as well as low-power consumption. However, before mapping algorithms on the accelerator, application developers require sufficient knowledge of the hardware organization and specially designed instructions. They also need significant effort to tune the code for improving execution efficiency when no well-designed compiler or library is available. To address this problem, we focus on library support for stencil (nearest-neighbor) computations that represent a class of algorithms commonly used in many partial differential equation (PDE) solvers. In this research, we address the following topics: (1) system configuration, features, and mnemonics of EMAX; (2) instruction mapping techniques that reduce the amount of data to be read from the main memory; (3) performance evaluation of the library for PDE solvers. With the features of a library that can reuse the local data across the outer loop iterations and map many instructions by unrolling the outer loops, the amount of data to be read from the main memory is significantly reduced to a minimum of 1/7 compared with a hand-tuned code. In addition, the stencil library reduced the execution time 23% more than a general-purpose processor.

An earthquake is a destructive natural disaster, which cannot be predicted accurately and causes devastating damage and losses. In fact, many of the damages can be prevented if people know what to do during and after earthquakes. Earthquake education is the most important method to raise public awareness and mitigate the damage caused by earthquakes. Generally, earthquake education consists of conducting traditional earthquake drills in schools or communities and experiencing an earthquake through the use of an earthquake simulator. However, these approaches are unrealistic or expensive to apply, especially in underdeveloped areas where earthquakes occur frequently. In this paper, an earthquake drill simulation system based on virtual reality (VR) technology is proposed. A User is immersed in a 3D virtual earthquake environment through a head mounted display and is able to control the avatar in a virtual scene via Kinect to respond to the simulated earthquake environment generated by SIGVerse, a simulation platform. It is a cost effective solution and is easy to deploy. The design and implementation of this VR system is proposed and a dormitory earthquake simulation is conducted. Results show that powerful earthquakes can be simulated successfully and the VR technology can be applied in the earthquake drills.

This paper proposes a novel direction-of-arrival (DOA) estimation method that can reduce performance degradation due to angular spread. Some algorithms previously proposed for such estimation make assumptions about the distributions of amplitude and phase for incident waves because most DOA estimation algorithms are sensitive to angular spread. However, when the assumptions are inaccurate, these algorithms perform poorly as compared with algorithms without countermeasures against angular spread. In this paper, we propose a method for selecting an appropriate DOA estimation algorithm according to the channel vector of each source signal as estimated by independent component analysis. Computer simulations show that the proposed method can robustly estimate DOA in environments with angular spread.

This paper reviews a recent progress in terahertz wireless communications enabled by photonics technologies. After briefly summarizing transceiver configurations with electronics and photonics technologies, photonics-based approaches to achieving over 100-Gbit/s data rates are discussed. Then, some of our updated results on real-time wireless transmission experiments using discrete components are shown at data rates up to 50 Gbit/s. Finally, integration technologies are described by demonstrating latest advances in integrated optical sources and transmitters.

This report describes an all-digital phase-locked loop (ADPLL) using a temperature compensated settling time reduction technique. The novelty of this work is autonomous oscillation control word estimation without a look-up table or memory circuits. The proposed ADPLL employs a multi-phase digitally controlled oscillator (DCO). In the proposed estimation method, the optimum oscillator tuning word (OTW) is estimated from the DCO frequency characteristic in the setup phase of ADPLL. The proposed ADPLL, which occupies 0.27×0.36mm2, is fabricated by a 65 nm CMOS process. The temperature compensation PLL controller (TCPC) is implemented using an FPGA. Although the proposed method has 20% area overhead, measurement results show that the 47% settling time is reduced. The average settling time at 25°C is 3µs. The average reduction energy is at least 42% from 0°C to 100°C.

In this paper, we propose Configurable Query Processing Hardware (CQPH), an FPGA-based accelerator for continuous query processing over data streams. CQPH is a highly optimized and minimal-overhead execution engine designed to deliver real-time response for high-volume data streams. Unlike most of the other FPGA-based approaches, CQPH provides on-the-fly configurability for multiple queries with its own dynamic configuration mechanism. With a dedicated query compiler, SQL-like queries can be easily configured into CQPH at run time. CQPH supports continuous queries including selection, group-by operation and sliding-window aggregation with a large number of overlapping sliding windows. As a proof of concept, a prototype of CQPH is implemented on an FPGA platform for a case study. Evaluation results indicate that a given query can be configured within just a few microseconds, and the prototype implementation of CQPH can process over 150 million tuples per second with a latency of less than a microsecond. Results also indicate that CQPH provides linear scalability to increase its flexibility (i.e., on-the-fly configurability) without sacrificing performance (i.e., maximum allowable clock speed).

In this paper, we propose a localization algorithm that uses the time difference of arrival (TDOA) and the angle of arrival (AOA). The problem is formulated in a hybrid linear matrix equation. TDOA and AOA measurements are used for estimating the target's position. Although it is known that the accuracy of TDOA based localization is superior to that of AOA based localization, TDOA based localization has a poor vertical accuracy in deteriorated geometrical conditions. This paper, therefore, proposes a localization algorithm in which the vertical position is estimated by AOA measurements and the horizontal position is estimated by TDOA measurement in order to achieve high location accuracy in three dimensions. In addition, the Lagrange multipliers are obtained efficiently and robustly. The simulation analysis shows that the proposed constrained linear squares (CLS) algorithm is an unbiased estimator, and that it approaches the Cramer-Rao lower bound (CRLB) when the measurement noise and the sensor's location errors are sufficiently small.

An effective time-step control method is proposed for the damped pseudo-transient analysis (DPTA). This method is based on the idea of the switched evolution/relaxation method which can automatically adapt the step size for different circuit states. Considering the number of iterations needed for the convergence of the Newton-Raphson method, the new method adapts the suitable time-step size with the status of previous steps. By numerical examples, it is proved that this method can improve the simulation efficiency and convergence for the DPTA method to solve nonlinear DC circuits.

The conical area evolutionary algorithm (CAEA) has a very high run-time efficiency for bi-objective optimization, but it can not tackle problems with more than two objectives. In this letter, a conical hypervolume evolutionary algorithm (CHEA) is proposed to extend the CAEA to a higher dimensional objective space. CHEA partitions objective spaces into a series of conical subregions and retains only one elitist individual for every subregion within a compact elitist archive. Additionally, each offspring needs to be compared only with the elitist individual in the same subregion in terms of the local hypervolume scalar indicator. Experimental results on 5-objective test problems have revealed that CHEA can obtain the satisfactory overall performance on both run-time efficiency and solution quality.

The pilot symbols in the broadband Air-to-Ground (A/G) communications system, e.g., L-band Digital Aeronautical Communications System (L-DACS1), are expected to be also utilized for navigation. In order to identify the co-channel signals from different Ground Stations (GSs), the N-Shift Zero Correlation Zone (NS-ZCZ) sequences are employed for pilot sequences. The ideal correlation property of the proposed pilot sequence in ZCZ can maintain the signal with less co-channel interference. The simulation confirms that the more co-channel GSs are employed, the higher navigation accuracy can be achieved.

Orthogonal frequency division multiplexing (OFDM) channel estimation is the key technique used in broadband wireless networks. The Doppler frequency caused by fast mobility environments will cause inter-carrier interference (ICI) and degrade the performance of OFDM systems. Due to the severe ICI, channel estimation becomes a difficult task in higher mobility scenarios. Our aim is to propose a pilot-aided channel estimation method that is robust to high Doppler frequency with low computational complexity and pilot overheads. In this paper, the time duration of each estimate covers multiple consecutive OFDM symbols, named a “window”. A close-form of polynomial channel modeling is derived. The proposed method is initialized to the least squares (LS) estimates of the channels corresponding to the time interval of the pilot symbols within the window. Then, the channel interpolation is performed in the entire window. The results of computer simulations and computation complexity evaluations show that the proposed technique is robust to high Doppler frequency with low computation complexity and low pilot overheads. Compared with the state-of-the-art method and some conventional methods, the new technique proposed here has much lower computational complexity while offering comparable performance.

Amplify-and-forward (AF) relay multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems can achieve high data rate and high quality communications. On the other hand, it has to estimate all channels between the source-relay and relay-destination nodes in the destination node. In MIMO/OFDM systems, high time resolution carrier interferometry (HTRCI) has been proposed to achieve an accurate channel estimation (CE) with a small number of pilot signals. However, since it has many interferences, an accurate CE is not obtained and the system performance is degraded in AF relay MIMO/OFDM systems. Therefore, in this paper, we propose the complex HTRCI (C-HTRCI) pilot signal and the enhanced minimum mean square error (E-MMSE) equalization to achieve an accurate CE and to improve the system performance for AF relay MIMO/OFDM systems.

This letter presents a two-stage method to extend the degenerate unmixing estimation technique (DUET) for reverberant speech separation. First, frequency-bin-wise attenuation and delay parameters are introduced and estimated by online update rules, to handle early reflections. Next, a mask reestimation algorithm based on the precedence effect is developed to detect and fix the errors on binary masks caused by late reflections. Experimental results demonstrate that the proposed method improves separation performance significantly.

Multi-layer transport networks that utilize sub-lambda paths over a wavelength path have been shown to be effective in accommodating traffic with various levels of granularity. For different service requirements, a virtualized network was proposed where the infrastructure is virtually sliced to accommodate different levels of reliability. On the other hand, network reconfiguration is a promising candidate for quasi-dynamic and multi-granular traffic. Reconfiguration, however, incurs some risks such as service disruption and fluctuations in delay. There has not yet been any study on accommodating and reconfiguring paths according to different service classes in multi-layer transport networks. In this paper, we propose differentiated reconfiguration to address the trade-off relationship between accommodation efficiency and disruption risk in virtualized multi-layer transport networks that considers service classes defined as a combination of including or excluding a secondary path and allowing or not allowing reconfiguration. To implement the proposed network, we propose a multi-layer redundant path accommodation design and reconfiguration algorithm. A reliability evaluation algorithm is also introduced. Numerical evaluations show that when all classes are divided equally, equipment cost can be reduced approximately by 6%. The proposed reconfigurable networks are shown to be a cost effective solution that maintains reliability.

The advanced front-end (AFE) for automatic speech recognition (ASR) was standardized by the European Telecommunications Standards Institute (ETSI). The AFE provides speech enhancement realized by an iterative Wiener filter (IWF) in which a smoothed FFT spectrum over adjacent frames is used to design the filter. We have previously proposed robust time-varying complex Auto-Regressive (TV-CAR) speech analysis for an analytic signal and evaluated the performance of speech processing such as F0 estimation and speech enhancement. TV-CAR analysis can estimate more accurate spectrum than FFT, especially in low frequencies because of the nature of the analytic signal. In addition, TV-CAR can estimate more accurate speech spectrum against additive noise. In this paper, a time-invariant version of wide-band TV-CAR analysis is introduced to the IWF in the AFE and is evaluated using the CENSREC-2 database and its baseline script.