In the localization systems based on time difference of arrival (TDOA), multipath fading and the interference source will deteriorate the localization performance. In response to this situation, TDOA estimation based on blind beamforming is proposed in the frequency domain. An additional constraint condition is designed for blind beamforming based on maximum power collecting (MPC). The relationship between the weight coefficients of the beamformer and TDOA is revealed. According to this relationship, TDOA is estimated by discrete Fourier transform (DFT). The efficiency of the proposed estimator is demonstrated by simulation results.

This paper describes an evaluation of a temporally stable spectral envelope estimator proposed in our past research. The past research demonstrated that the proposed algorithm can synthesize speech that is as natural as the input speech. This paper focuses on an objective comparison, in which the proposed algorithm is compared with two modern estimation algorithms in terms of estimation performance and temporal stability. The results show that the proposed algorithm is superior to the others in both aspects.

With the development and diverse use of wireless radio terminals, it is necessary to estimate the specific absorption rate (SAR) of the human body from such devices under various exposure situations. In particular, tablet computers may be used for a long time while placed near the abdomen. There has been insufficient evaluation of the SAR for the human body from tablet computers. Therefore, we investigated the SAR of various configurations of a commercial tablet computer using a numerical model with the anatomical structures of Japanese males and females, respectively. We find that the 10-g-averaged SAR of the tablet computer is strongly altered by the tablet's orientation, i.e., from -7.3dB to -22.6dB. When the tablet computer is moved parallel to the height direction, the relative standard deviations of the 10-g averaged SAR for the male and female models are within 40%. In addition, those for the different tilts of the computer are within 20%. The fluctuations of the 10-g-averaged SAR for the seated human models are within ±1.5dB in all cases.

This paper proposes an updating state dependent disturbance observer (USDDOB) to reject position dependent disturbances when parameters vary slowly, and input and output are time-delayed. To reject the effects of resultant slowly-varying position dependent disturbances, the USDDOB uses the control method of the state dependent disturbance observer (SDDOB) and time-invariance approximation. The USDDOB and a main proportional integral (PI) controller constitute a robust controller. Simulations and experiments using a 1-degree-of-freedom (1-DOF) tilted planar robot show the effectiveness of the proposed method.

This paper presents comprehensive comparisons on the block error rate (BLER) performance of rate-one open-loop (OL) transmit diversity schemes with four antennas for discrete Fourier transform (DFT)-precoded Orthogonal Frequency Division Multiple Access (OFDMA). One candidate scheme employs a quasi-orthogonal (QO) - space-time block code (STBC) in which four-branch minimum mean-square error (MMSE) combining is achieved at the cost of residual inter-code interference (ICI). Another candidate employs a combination of the STBC and selection transmit diversity called time switched transmit diversity (TSTD) (or frequency switched transmit diversity (FSTD)). We apply a turbo frequency domain equalizer (FDE) associated with iterative decision-feedback channel estimation (DFCE) using soft-symbol estimation to reduce channel estimation (CE) error. The turbo FDE includes an ICI canceller to reduce the influence of the residual ICI for the QO-STBC. Based on link-level simulation results, we show that a combination of the STBC and TSTD (or FSTD) is suitable as a four-antenna OL transmit diversity scheme for DFT-precoded OFDMA using the turbo FDE and iterative DFCE.

A term tree pattern is a rooted ordered tree pattern which consists of ordered tree structures with edge labels and structured variables with labels. All variables with the same label in a term tree pattern can be simultaneously replaced with ordered trees isomorphic to the same rooted ordered tree. Then, a term tree pattern is suitable for representing structural features common to tree structured data such as XML documents on the web, the secondary structures of RNA in biology and parse trees describing grammatical structures of natural languages. Let $ott$ be the set of all term tree patterns which have one or more variables with the same label. Let $lott$ be the set of all term tree patterns t such that all variables in t have distinct labels. We remark that $lottsubsetneq ott$ holds. In this paper, we consider a problem, called Matching problem for term tree patterns, of deciding whether or not a given rooted ordered tree T is obtained from a given term tree pattern t by replacing variables in t with rooted ordered trees. We show that Matching problem for term tree patterns in $ott$ is NP-complete, by giving a reduction from the string pattern matching problem, which is NP-complete. Next, by giving operations on an interval, which is a set containing all integers between two given integers representing vertex identifiers, we propose an efficient algorithm for solving Matching problem for term tree patterns in $lottsubsetneq ott$. Then, we show that, when an ordered tree having N vertices and a term tree pattern $t in lott$ having n vertices are given, the proposed matching algorithm correctly solves this problem in O(nN) time.

In recent years, hybrid typestate analysis has been proposed to eliminate unnecessary monitoring instrumentations for runtime monitors at compile-time. Nop-shadows Analysis (NSA) is one of these hybrid typestate analyses. Before generating residual monitors, NSA performs the data-flow analysis which is intra-procedural flow-sensitive and partially context-sensitive to improve runtime performance. Although NSA is precise, there are some cases on which it has little effects. In this paper, we propose three optimizations to further improve the precision of NSA. The first two optimizations try to filter interferential states of objects when determining whether a monitoring instrumentation is necessary. The third optimization refines the inter-procedural data-flow analysis induced by method invocations. We have integrated our optimizations into Clara and conducted extensive experiments on the DaCapo benchmark. The experimental results demonstrate that our first two optimizations can further remove unnecessary instrumentations after the original NSA in more than half of the cases, without a significant overhead. In addition, all the instrumentations can be removed for two cases, which implies the program satisfy the typestate property and is free of runtime monitoring. It comes as a surprise to us that the third optimization can only be effective on 8.7% cases. Finally, we analyze the experimental results and discuss the reasons why our optimizations fail to further eliminate unnecessary instrumentations in some special situations.

A binary tree is regarded as a prefix-free binary code, in which the weighted sum of the lengths of root-leaf paths is equal to the expected codeword length. Huffman's algorithm computes an optimal tree in O(n log n) time, where n is the number of leaves. The problem was later generalized by allowing each leaf to have its own function of its depth and setting the sum of the function values as the objective function. The generalized problem was proved to be NP-hard. In this paper we study the case where every function is a unit step function, that is, a function that takes a lower constant value if the depth does not exceed a threshold, and a higher constant value otherwise. We show that for this case, the problem can be solved in O(n log n) time, by reducing it to the Coin Collector's problem.

This paper studies the energy-saving problem in cognitive multicast orthogonal frequency-division multiplexing (OFDM) systems, for which a time-frequency two-dimensional model is established to enable the system energy conservation through joint temporal and spectral adaptations. The formulated two-dimensional problem, minimizing the total power consumption whilst guaranteeing the minimal-rate requirement for each multicast session and constraining the maximal perceived interference in each timeslot for the active primary user, is categorized as mixed integer non-convex programming, whose optimal solution is intractable in general. However, based on the time-sharing property, an asymptotically optimal algorithm is proposed by jointly iterating spectrum element (SE) assignment and power allocation. Moreover, a suboptimal algorithm, which carries out SE assignment and power allocation sequentially, is presented as well to reduce the computation complexity. Simulation results show the proposed joint algorithm can achieve the near-optimal solution, and the proposed sequential algorithm approximates to the joint one very well with a gap of less than 3%. Compared with the existing slot-by-slot energy-saving algorithms, the total power consumption is considerably decreased due to the combined exploitation of time and frequency dimensions.

In the traditional time delay estimation methods, it is usually implicitly assumed that the observed signals are either only direct path propagate or coherently received. In practice, the multipath propagation and incoherent reception always exist simultaneously. In response to this situation, the joint maximum likelihood (ML) estimation of multipath delays and system error is proposed, and the estimation of the number of multipath is considered as well for the specific incoherent signal model. Furthermore, an algorithm based Gibbs sampling is developed to solve the multi-dimensional nonlinear ML estimation. The efficiency of the proposed estimator is demonstrated by simulation results.

Recently, the growing concepts that information communication technologies apply to social infrastructures have caused deep interests with wireless sensor networks (WSNs). WSNs can be used for various application areas such as home, health, factory and so on. For the different application areas, there are different technical issues (e.g., security, reliability, real time gathering, long life time, scalability). Efficient information gathering can be potentially obtained if we take a suitable information gathering method with considering the requirements of each WSN application. Thus, we have not persisted all information gathering perfectly and have proposed one of simple information gathering methods in response to the requirements of WSN applications in this paper. In the proposed method, the information is converted to physical-layer parameters of wireless communications, such as frequency and time. Also, simulations are performed to validate the effectiveness of the proposed method in real time gathering and estimating with high precision.

Accuracy of a method for analyzing the interface defect properties; time-domain charge pumping method, is evaluated. The method monitors the charge pumping (CP) current in time domain, and thus we expect that it gives us a noble way to investigate the interface state properties. In this study, for the purpose of evaluating the accuracy of the method, the interface state density extracted from the time-domain data is compared with that measured using the conventional CP method. The results show that they are equal to each other for all measured devices with various defect densities, demonstrating that the time-domain CP method is sufficiently accurate for the defect density evaluation.

In this paper, an energy harvesting architecture in an Underlay Cooperative Cognitive Network (UCCN) is investigated, in which power constrained Decode-and-Forward relays harvest energy from radio-frequency signals received from a source, and then consume the harvested energy by forwarding the recoded signals to their destination. These recoded signals are launched by a transmitting power which is the harvested energy per a time interval. Based on the energy harvesting architectures that have been studied, two operation protocols are proposed: UCCN with Power Splitting architecture (UCCN-PS), and UCCN with Time Switching architecture (UCCN-TS). The best cooperative relay in both protocols is taken to be the one that satisfies the following conditions: maximum harvested energy, and maximum decoding capacity. As a result of the best relay selection, the signal quality of the selected link from the best relay to the destination is enhanced by the maximum harvested energy. The system performance of the secondary network in the UCCN-PS and UCCN-TS protocols is analyzed and evaluated by the exact closed-form outage probabilities and throughput analyses over Rayleigh fading channels. The Monte Carlo simulation method is performed to verify the theoretical expressions. Evaluations based on outage probability and throughput show that the system performance of the secondary network in the UCCN-PS and UCCN-TS protocols improves when the number of cooperative relays and the interference constraint increase as well as when the primary receiver is farther from the transmitting nodes such as the source and relays of the secondary network. In addition, the throughput performance of the UCCN-PS protocol outperforms that of the UCCN-TS protocol. Finally, the effects of the power splitting ratio, energy harvesting time, energy conversion efficiency, target Signal-to-Noise Ratio (SNR), and location of cooperative relays on the system performance of the secondary network are presented and discussed.

Recommendation systems have been widely used in E-commerce sites, social media and etc. An important recommendation task is to predict items that a user will perform actions on with users' historical data, which is called top-K recommendation. Recently, there is huge amount of emerging items which are divided into a variety of categories and researchers have argued or suggested that top-K recommendation of item category could be very beneficial for users to make better and faster decisions. However, the traditional methods encounter some common but crucial problems in this scenario because additional information, such as time, is ignored. The ranking algorithm on graphs and the increasingly growing amount of online user behaviors shed some light on these problems. We propose a construction method of time-aware graphs to use ranking algorithm for personalized recommendation of item category. Experimental results on real-world datasets demonstrate the advantages of our proposed method over competitive baseline algorithms.

A robust time synchronization algorithm is proposed for orthogonal frequency division multiplexing (OFDM) based aeronautical mobile airport communication systems (AeroMACS). Using a very sharp timing metric obtained from the preamble, the proposed algorithm shows very robust time synchronization performance for various channel models in an airport. Simulation results show that the proposed algorithm achieves an SNR gain of 2 to 3dB at the failure rate of 10-2 to 10-3 compared with previous algorithms.

Detecting traffic anomalies is an indispensable component of overall security architecture. As Internet and traffic data with more sophisticated attacks grow exponentially, preserving security with signature-based traffic analyzers or analyzers that do not support massive traffic are not sufficient. In this paper, we propose a novel method based on combined sketch technique and S-transform analysis for detecting anomalies in massive traffic streams. The method does not require any prior knowledge such as attack patterns and models representing normal traffic behavior. To detect anomalies, we summarize the entropy of traffic data over time and maintain the summarized data in sketches. The entropy fluctuation of the traffic data aggregated to the same bucket is observed by S-transform to detect spectral changes referred to as anomalies in this work. We evaluated the performance of the method with real-world backbone traffic collected at the United States and Japan transit link in terms of both accuracy and false positive rates. We also explored the method parameters' influence on detection performance. Furthermore, we compared the performance of our method to S-transform-based and Wavelet-based methods. The results demonstrated that our method was capable of detecting anomalies and overcame both methods. We also found that our method was not sensitive to its parameter settings.

Users of wireless mobile devices need Internet access not only when they stay at home or office, but also when they travel. It may be desirable for such users to select a "longcut route" from their current location to his/her destination that has longer travel time than the shortest route, but provides a better mobile wireless environment. In this paper, we formulate the above situation as the optimization problem of “optimal longcut route selection”, which requires us to find the best route concerning the wireless environment subject to a travel time constraint. For this new problem, we show NP-hardness, propose two pseudo-polynomial time algorithms, and experimental evaluation of the algorithms.

This paper develops the double generating function method for the discrete-time linear quadratic optimal control problem. This method can give generators for optimal solutions only in terms of pre-computed coefficients and boundary conditions, which is useful for the on-line repetitive computation for different boundary conditions. Moreover, since each generator contains inverse terms, the invertibility analysis is also performed to conclude that the terms in the generators constructed by double generating functions with opposite time directions are invertible under some mild conditions, while the terms with the same time directions will become singular when the time goes infinity which may cause instability in numerical computations. Examples demonstrate the effectiveness of the developed method.

Content caching networks like Information-Centric Networking (ICN) are beneficial to reduce the network traffic by storing content data on routers near to users. In ICN, it becomes an important issue to manage system resources, such as storage and network bandwidth, which are influenced by cache characteristics of each cache node. Meanwhile, cache aging techniques based on Time-To-Live (TTL) of content facilitate analyzing cache characteristics and can realize appropriate resource management by setting efficient TTLs. However, it is difficult to search for the efficient TTLs in a distributed cache system connected by multiple cache nodes. Therefore, we propose an adaptive control mechanism of the TTL value of content in distributed cache systems by using predictive models which can estimate the impact of the TTL values on network resources and cache performance. Furthermore, we show the effectiveness of the proposed mechanism.

Forty years after the first application of Superconducting Quantum Interference Devices (SQUIDs) [1], [2] for geophysical purposes, they have recently become a valued tool for mineral exploration. One of the most common applications is time domain (or transient) electromagnetics (TEM), an active method, where the inductive response from the ground to a changing current (mostly rectangular) in a loop on the surface is measured. After the current in the transmitter coil is switched, eddy currents are excited in the ground, which decay in a manner dependent on the conductivity of the underlying geologic structure. The resulting secondary magnetic field at the surface is measured during the off-time by a receiver coil (induced voltage) or by a magnetometer (e.g. SQUID or fluxgate). The recorded transient signal quality is improved by stacking positive and negative decays. Alternatively, the TEM results can be inverted and give the electric conductivity of the ground over depth. Since SQUIDs measure the magnetic field with high sensitivity and a constant frequency transfer function, they show a superior performance compared to conventional induction coils, especially in the presence of strong conductors. As the primary field, and especially its slew rate, are quite large, SQUID systems need to have a large slew rate and dynamic range. Any flux jump would make the use of standard stacking algorithms impossible. IPHT and Supracon are developing and producing SQUID systems based on low temperature superconductors (LTS, in our case niobium), which are now state-of-the-art. Due to the large demand, we are additionally supplying systems with high temperature superconductors (HTS, in our case YBCO). While the low temperature SQUID systems have a better performance (noise and slew rate), the high temperature SQUID systems are easier to handle in the field. The superior performance of SQUIDs compared to induction coils is the most important factor for the detection of good conductors at large depth or ore bodies underneath conductive overburden.