Cardinality estimation schemes of Radio Frequency IDentification (RFID) tags using Framed Slotted ALOHA (FSA) based protocol are studied in this paper. Not as same as previous estimation schemes, we consider tag cardinality estimation problem under not only detection errors but also capture effect, where a tag's IDentity (ID) might not be detected even in a singleton slot, while it might be identified even in a collision slot due to the fading of wireless channels. Maximum Likelihood (ML) approach is utilized for the estimation of the detection error probability, the capture effect probability, and the tag cardinality. The performance of the proposed method is evaluated under different system parameters via computer simulations to show the method's effectiveness comparing to other conventional approaches.

With the successful adoption of link analysis techniques such as PageRank and web spam filtering, current web search engines well support “navigational search”. However, due to the use of a simple conjunctive Boolean filter in addition to the inappropriateness of user queries, such an engine does not necessarily well support “informational search”. Informational search would be better handled by a web search engine using an informational retrieval model combined with enhancement techniques such as query expansion and relevance feedback. Moreover, the realization of such an engine requires a method to prosess the model efficiently. In this paper we propose a novel extension of an existing top-k query processing technique to improve search efficiency. We add to it the technique utilizing a simple data structure called a “term-document binary matrix,” resulting in more efficient evaluation of top-k queries even when the queries have been expanded. We show on the basis of experimental evaluation using the TREC GOV2 data set and expanded versions of the evaluation queries attached to this data set that the proposed method can speed up evaluation considerably compared with existing techniques especially when the number of query terms gets larger.

IEEE802.11 Wireless Local Area Networks (WLANs) are becoming more and more pervasive due to their simple channel access mechanism, Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA), but this mechanism provides all nodes including Access Point and other Stations with the same channel access probability. This characteristic does not suit the infrastructure mode which has so many downlink flows to be transmitted at the Access Point that congestion at the Access Point is more likely to occur. To resolve this asymmetry traffic problem, we develop an Optimal Contention Window Adjustment method assuming the condition of erroneous channels over WLANs. This method can be easily implemented and is compatible with the original CSMA/CA mechanism. It holds the ratio of downlink and uplink flows and at the same time achieves the maximum saturation throughput in the WLANs. We use the Markov Chain analytical model to analyze its performance and validate it through the simulations.

Recently, probabilistic topic models have been applied to various types of data, including text, and their effectiveness has been demonstrated. Latent Dirichlet allocation (LDA) is a well known topic model. Variational Bayesian inference or collapsed Gibbs sampling is often used to estimate parameters in LDA; however, these inference methods incur high computational cost for large-scale data. Therefore, highly efficient technology is needed for this purpose. We use parallel computation technology for efficient collapsed Gibbs sampling inference for LDA. We assume a symmetric multiprocessing (SMP) cluster, which has been widely used in recent years. In prior work on parallel inference for LDA, either MPI or OpenMP has often been used alone. For an SMP cluster, however, it is more suitable to adopt hybrid parallelization that uses message passing for communication between SMP nodes and loop directives for parallelization within each SMP node. We developed an MPI/OpenMP hybrid parallel inference method for LDA, and evaluated the performance of the inference under various settings of an SMP cluster. We further investigated the approximation that controls the inter-node communications, and found out that it achieved noticeable increase in inference speed while maintaining inference accuracy.

Automatic modulation classification (AMC) is an important function of radio surveillance systems in order to identify unknown signals. Many previous works on AMC have utilized signal cyclostationarity, particularly spectral correlation density (SCD), but many of them fail to address several implementation issues, such as the assumption of perfect knowledge of the symbol rate. In this paper, we discuss several practical issues, e.g. cyclic frequency mismatch, which may affect the SCD, and propose compensation techniques to overcome those issues. We also propose a novel feature extraction technique from the SCD, which utilizes the SCD of not only the original received signal, but also the squared received signal. A symbol rate estimation technique which complements the feature extraction is also proposed. Finally, the classification performance of the system is evaluated through Monte Carlo simulations using a wide variety of modulated signals, and simulation results show that the proposed technique can estimate the symbol rate and classify modulation with a probability of above 0.9 down to SNRs of 5 dB.

Turbo equalization is an iterative equalization and decoding technique that can achieve impressive performance gains for communication systems. In this letter, we investigate the turbo equalization method for the decoding of the Davey-MacKay (DM) construction over the IDS-AWGN channels, which indicates a cascaded insertion, deletion, substitution (IDS) channel and an additive white Gaussian noise (AWGN) channel. The inner decoder for the DM construction can be seen as an maximum a-posteriori (MAP) detector. It receives the beliefs generated by the outer LDPC decoder when turbo equalization is used. Two decoding schemes with different kinds of inner decoders, namely hard-input inner decoder and soft-input inner decoder, are investigated. Simulation results show that significant performance gains are obtained for both decoders with respect to the insertion/deletion probability at different SNR values.

Recent interest in wireless power transfer research has been attracting a great deal of attention. To transfer power efficiently and safely in wireless power transfer system, information, such as frequency, required power and element values, need to be transmitted reliably. However, the bandwidth, which is used for exchanging information, is affected by the change of load at the receiver when it is charging. This paper investigates the effect of load fluctuation in data communication using orthogonal frequency division multiplexing (OFDM) modulation in resonant-type wireless power transfer systems. The equivalent circuit used in the transmitting and receiving antennas is a band pass filter (BPF) and its bandwidth is evaluated through circuit simulations. Numerical results obtained through computer simulation show that the bit error rate (BER) performance is affected by the load fluctuation and the efficiency of power transfer.

This paper describes an overview of demands on wireless communications from the point of view of robotics, oceanics and aviation technologies. These technologies are mostly applied to extreme environments, where humans cannot easily approach and directly operate equipment. In such environments, reliable and robust wireless communications are highly required to perform missions perfectly. However, there are many issues for wireless technologies to meet those requirements due to poor propagation and large delay conditions. This paper discusses wireless communication technologies required in land-sea-and-air environments based on the recent development challenges of unmanned ground and marine robots and next-generation air-transportation systems. This paper will contribute future wireless communication techniques for unmanned robots and next-generation aviations.

This paper presents a method for learning an overcomplete, nonnegative dictionary and for obtaining the corresponding coefficients so that a group of nonnegative signals can be sparsely represented by them. This is accomplished by posing the learning as a problem of nonnegative matrix factorization (NMF) with maximization of the incoherence of the dictionary and of the sparsity of coefficients. By incorporating a dictionary-incoherence penalty and a sparsity penalty in the NMF formulation and then adopting a hierarchically alternating optimization strategy, we show that the problem can be cast as two sequential optimal problems of quadratic functions. Each optimal problem can be solved explicitly so that the whole problem can be efficiently solved, which leads to the proposed algorithm, i.e., sparse hierarchical alternating least squares (SHALS). The SHALS algorithm is structured by iteratively solving the two optimal problems, corresponding to the learning process of the dictionary and to the estimating process of the coefficients for reconstructing the signals. Numerical experiments demonstrate that the new algorithm performs better than the nonnegative K-SVD (NN-KSVD) algorithm and several other famous algorithms, and its computational cost is remarkably lower than the compared algorithms.

Reliable broadcasting in vehicular ad-hoc networks is challenging due to their unique characteristics including intermittent connectivity and various vehicular scenarios. Applications and services in intelligent transportation systems need an efficient, fast and reliable broadcasting protocol especially for safety and emergency applications. In our previous work, we have proposed DECA, a new reliable broadcasting protocol which suits such characteristics. To address the issue of various vehicular scenarios, our protocol performs beaconing to gather local density information of 1-hop neighbors and uses such information to adapt its broadcasting decision dynamically. Specifically, before broadcasting a message, a node selects a neighbor with the highest density and adds the selected neighbor's identifier to the message. Upon receiving of a broadcast message, each node checks whether or not it is the selected neighbor. If so, it is responsible for rebroadcasting the message immediately. This mechanism can raise the data dissemination speed of our protocol so that it is as fast as simple flooding. To address the issue of intermittent connectivity, identifiers of broadcast messages are added into beacons. This helps nodes to check if there are any broadcast messages that have not yet been received. In this paper, we propose DECA with a new beaconing algorithm and a new waiting timeout calculation, so-called DECA-bewa. Our new protocol can reduce redundant retransmissions and overall overhead in high density areas. The protocol performance is evaluated on the network simulator (NS-2). Simulation results show that DECA-bewa outperforms existing protocols in terms of reliability, overhead and speed of data dissemination.

A modified modeling of residue effect on nano-electro-mechanical nonvolatile memory (NEMory) is presented for considering wet etching process. The effect of a residue under the cantilever is investigated for the optimization. The feasibility of the proposed model is investigated by finite element analysis simulations.

It is known that demand and supply power balancing is an essential method to operate power delivery system and prevent blackouts caused by power shortage. In this paper, we focus on the implementation of demand response strategy to save power during peak hours by using Smart Grid. It is obviously impractical with centralized power control network to realize the real-time control performance, where a single central controller measures the huge metering data and sends control command back to all customers. For that purpose, we propose a new architecture of hierarchical distributed power control network which is scalable regardless of the network size. The sub-controllers are introduced to partition the large system into smaller distributed clusters where low-latency local feedback power control loops are conducted to guarantee control stability. Furthermore, sub-controllers are stacked up in an hierarchical manner such that data are fed back layer-by-layer in the inbound while in the outbound control responses are decentralized in each local sub-controller for realizing the global objectives. Numerical simulations in a realistic scenario of up to 5000 consumers show the effectiveness of the proposed scheme to achieve a desired 10% peak power saving by using off-the-shelf wireless devices with IEEE802.15.4g standard. In addition, a small-scale power control system for green building test-bed is implemented to demonstrate the potential use of the proposed scheme for power saving in real life.

In this paper, we consider the XPath satisfiability problem under restricted DTDs called “duplicate free”. For an XPath expression q and a DTD D, q is satisfiable under D if there exists an XML document t such that t is valid against D and that the answer of q on t is nonempty. Evaluating an unsatisfiable XPath expression is meaningless, since such an expression can always be replaced by an empty set without evaluating it. However, it is shown that the XPath satisfiability problem is intractable for a large number of XPath fragments. In this paper, we consider simple XPath fragments under two restrictions: (i) only a label can be specified as a node test and (ii) operators such as qualifier ([]) and path union (∪) are not allowed. We first show that, for some small XPath fragments under the above restrictions, the satisfiability problem is NP-complete under DTDs without any restriction. Then we show that there exist XPath fragments, containing the above small fragments, for which the satisfiability problem is in PTIME under duplicate-free DTDs.

A use of ultra wideband (UWB) technology within spacecrafts has been proposed with a view to partially replacing wired interface buses with wireless connections. Adoption of wireless technologies within the spacecrafts could contribute to reduction in cable weight (and launching cost as a result), reduction in the cost of manufacture, more flexibility in layout of spacecraft subsystems, and reliable connections at rotary, moving, and sliding joints. However, multipath propagation in semi-closed conductive enclosures, such as spacecrafts, restricts the link performance. In this paper, UWB and narrowband propagation were measured in a UWB frequency band (from 3.1 to 10.6 GHz, the full-band UWB approved in the United States) within a small spacecrafts and a shield box of the same size. While narrowband propagation resulted in considerable spatial variations in propagation gain due to interferences caused by multipath environments, UWB yielded none. This implies that the UWB systems have an advantage over narrowband from a viewpoint of reducing fading margins. Throughputs exceeding 80 Mb/s were obtained by means of commercially-available UWB devices in the spacecraft. Path gains and throughputs were also measured for various antenna settings and polarizations. Polarization configurations were found to produce almost no effect on average power delay profiles and substantially small effects on the throughputs. Significantly long delay spreads and thus limited link performance are caused by a conductive enclosure (the shield box) without apertures on the surfaces. Even in such an environment, it was found that delay spreads can be suppressed by partially paneling a radio absorber on the inner surfaces. More than 96 Mb/s throughputs were attained when the absorber panel covered typically 4% of the total inner surface area.

A method for the specification of weighting functions for a spaceborne/airborne interferometric synthetic aperture radar (SAR) sensor for Earth observation and environment monitoring is introduced. This method is based on designing an optimum mismatched filter which minimizes the total power in sidelobes located out of a specified range region around the peak value point of the system point-target response, i.e. impulse response function under the constraint imposed on the peak value. It is shown that this method allows achieving appreciable improvement in accuracy performance without degradation in the range resolution.

To mitigate the inter-cell interference in multicell downlink systems, this letter consider the robust precoder design for multicell cooperation where the knowledge of channel state available at the base station is imperfect. Assuming that imperfect channel state information (CSI) can be exchanged among cells but with no data sharing, we investigate the worst-case performance optimization problem with bounded CSI error. Our objective is to minimize the weighted sum mean-square-error (MSE) subject to per-base-station power constraints. A distributed solution is obtained by reformulating the upper bound of MSE and exploiting the Lagrangian method for the optimal problem. Simulation results demonstrate that the proposed algorithm is robust to guarantee the worst-case sum rate performance and has lower computational complexity than the SINR-based design.

The application of information hiding to image compression is investigated to improve compression efficiency for JPEG color images. In the proposed method, entropy-coded DCT coefficients of chrominance components are embedded into DCT coefficients of the luminance component. To recover an image in the face of the degradation caused by compression and embedding, an image restoration method is also applied. Experiments show that the use of both information hiding and image restoration is most effective to improve compression efficiency.

In summary, we successfully fabricated the nonvolatile hybrid polymer 4F2 memory-cell. It was based on bistable state, which was observed in PS layer that is containing a Ni nanocrystals capped with NiO tunneling barrier sandwiched by Al electrodes. The current conduction mechanism for polymer memory-cell was demonstrated by fitting the I-V curves. The electrons were charged and discharged on Ni nanocrystals by tunneling through the NiO tunneling barrier. In addition, the memory-cell showed a good and reproducible nonvolatile memory-cell characteristic. Its memory margin is about 1.410. The retention-time is more than 105 seconds and the endurance cycles of program-and-erase is more than 250 cycles. Furthermore, Thefore, polymer memory-cell would be good candidates for nonvolatile 4F2 cross-bar memory-cell.

Ultra-wideband (UWB) pulse radar has high range resolution and permeability in a dielectric medium, and has great potential for the non-destructive inspection or early-stage detection of breast cancer. As an accurate and high-resolution imaging method for targets embedded in a dielectric medium, extended range points migration (RPM) has been developed. Although this method offers an accurate internal target image in a homogeneous media, it assumes the permittivity of the dielectric medium is given, which is not practical for general applications. Although there are various permittivity estimation methods, they have essential problems that are not suitable for clear, dielectric boundaries like walls, or is not applicable to an unknown and arbitrary shape of dielectric medium. To overcome the above drawbacks, we newly propose a permittivity estimation method suitable for various shapes of dielectric media with a clear boundary, where the dielectric boundary points and their normal vectors are accurately determined by the original RPM method. In addition, our method iteratively compensates for the scattered waveform deformation using a finite-difference time domain (FDTD) method to enhance the accuracy of the permittivity estimation. Results from a numerical simulation demonstrate that our method achieves accurate permittivity estimation even for a dielectric medium of wavelength size.

An instrumental variable (IV) based linear estimator is proposed for effective target localization in sensor network by using time-difference-of-arrival (TDOA) measurement. Although some linear estimation approaches have been proposed in much literature, the target localization based on TDOA measurement still has a room for improvement. Therefore, we analyze the estimation errors of existing localization estimators such as the well-known quadratic correction least squares (QCLS) and the robust least squares (RoLS), and demonstrate advantages of the proposition by comparing the estimation errors mathematically and showing localization results through simulation. In addition, a recursive form of the proposition is derived to consider a real time application.