This paper presents design and analysis of an Automatic Repeat reQuest (ARQ) scheme for enhancing the throughput and reliability of broadband wireless access systems. The impact of ARQ is emphasized in terms of early error recovery, when Internet data applications and the TCP protocol are considered over a point-to-multipoint fixed wireless system. A selective repeat type ARQ scheme is designed and analyzed through extensive, realistic modeling and simulation of the entire network protocol stack and the wireless channel. The system-wide impact of ARQ design is quantified in terms of end-to-end delay, throughput and SNR gain and in all these metrics, significant performance improvement is observed. Enhanced features, namely, Segmentation and Reassembly (SAR) and Bitmap Compression, are proposed and shown to reduce the overhead costs.

Our research goal is to facilitate the sharing of stories with digital photographs. Some map websites now collect stories associated with peoples' relationships to places. Users map collections of places and include their intangible emotional associations with each location along with photographs, videos, etc. Though this framework of mapping stories is important, it is not sufficiently expressive to communicate stories in a narrative fashion. For example, when the number of the mapped collections of places is particularly large, it is neither easy for viewers to interpret the map nor is it easy for the creator to express a story as a series of events in the real world. This is because each narrative, in the form of a sequence of textual narratives, a sequence of photographs, a movie, or audio is mapped to just one point. As a result, it is up to the viewer to decide which points on the map must be read, and in what order. The conventional framework is fairly suitable for mapping and expressing fragments or snapshots of a whole story and not for conveying the whole story as a narrative using the entire map as the setting. We therefore propose a new framework, Spatial Slideshow, for mapping personal photo collections and representing them as stories such as route guidances, sightseeing guidances, historical topics, fieldwork records, personal diaries, and so on. It is a fusion of personal photo mapping and photo storytelling. Each story is conveyed through a sequence of mapped photographs, presented as a synchronized animation of a map and an enhanced photo slideshow. The main technical novelty of this paper is a method for creating three-dimensional animations of photographs that induce the visual effect of motion from photo to photo. We believe that the proposed framework may have considerable significance in facilitating the grassroots development of spatial content driven by visual communication concerning real-world locations or events.

In this paper, we propose a two-microphone noise reduction method to deal with non-stationary interfering noises in multiple-noise-source environments in which the traditional two-microphone algorithms cannot function well. In the proposed algorithm, multiple interfering noise sources are regarded as one virtually integrated noise source in each subband, and the spectrum of the integrated noise is then estimated using its virtual direction of arrival. To do this, we suggest a direction finder for the integrated noise using only two microphones that performs well even in speech active periods. The noise spectrum estimate is further improved by integrating a single-channel noise estimation approach and then subtracted from that of the noisy signal, finally enhancing the desired target signal. The performance of the proposed algorithm is evaluated and compared with the traditional algorithms in various conditions. Experimental results demonstrate that the proposed algorithm outperforms the traditional algorithms in various conditions in terms of objective and subjective speech quality measures.

In a centralized localization scenario, the limited throughput of the central node constrains the possible number of target node locations that can be estimated simultaneously. To overcome this limitation, we propose a method which effectively decreases the traffic load associated with target node localization, and therefore increases the possible number of target node locations that can estimated simultaneously in a localization system based on received signal strength indicator (RSSI) and maximum likelihood estimation. Our proposed method utilizes a threshold which limits the amount of forwarded RSSI data to the central node. As the threshold is crucial to the method, we further propose a method to theoretically determine its value. We experimentally verified the proposed method in various environments and the experimental results revealed that the method can reduce the load by 32-64% without significantly affecting the estimation accuracy.

A new unsupervised classification method is proposed for polarimetric SAR images to keep the spatial coherence of pixels and edges of different kinds of targets simultaneously. We consider the label scale variability of images by combining Inhomogeneous Markov Random Field (MRF) and Bayes' theorem. After minimizing an energy function using an expansion algorithm based on Graph Cuts, we can obtain classification results that are discontinuity preserving. Using a NASA/JPL AIRSAR image, we demonstrate the effectiveness of the proposed method.

A new type of humanoid robot arm which can coexist and be interactive with human beings are looked for. For the purpose of implementation of human smooth and fast movement to a pneumatic robot, the author used a humanoid robot arm with pneumatic agonist-antagonist actuators as endoskeletons which has control mechanism in the stiffness of each joint, and the controllability was experimentally discussed. Using Kitamori 's method to experimentally decide the control gains and using I-PD controller, three joints of the humanoid robot arm were experimentally controlled. The damping control algorithm was also adopted to the wrist joint, to modify the speed in accordance with the power. The results showed that the controllability to step-wise input was less than one degree in error to follow the target angles, and the time constant was less than one second. The simultaneous input of command to three joints was brought about the overshoot of about ten percent increase in error. The humanoid robot arm can generate the calligraphic motions, moving quickly at some times but slowly at other times, or particularly softly on some occasions but stiffly on other occasions at high accuracy.

The paper reviews recent advances in on-body antennas and propagation under a joint UK EPSRC research project between Queen Mary College, University of London and University of Birmingham. The study of on-body radio propagation has been extended by using various small antennas. The effect of antenna size, gain and radiation patterns on on-body channel characteristics has been studied. A practical wearable sensor antenna design is presented and it is demonstrated that a global simulation including sensor environment and human body is needed for accurate antenna characterisation. A 3D animation design software, POSER 6 has been used together with XFDTD to predict the on-body path loss variation due to changes in human postures and human motion. Finally, a preliminary study on the feasibility of a diversity scheme in an on-body environment has been carried out.

A deterministic pushdown automaton (dpda) having just one stack symbol is called a deterministic restricted one-counter automaton (droca). When it accepts an input by empty stack, it is called strict. This paper is concerned with a subclass of real-time strict droca's, called Szilard strict droca's, and studies the problem of identifying the subclass in the limit from positive data. The class of languages accepted by Szilard strict droca's coincides with the class of Szilard languages (or, associated languages) of strict droca's and is incomparable to each of the class of regular languages and that of simple languages. After providing some properties of languages accepted by Szilard strict droca's, we show that the class of Szilard strict droca's is polynomial time identifiable in the limit from positive data in the sense of Yokomori. This identifiability is proved by giving an exact characteristic sample of polynomial size for a language accepted by a Szilard strict droca. The class of very simple languages, which is a proper subclass of simple languages, is also proved to be polynomial time identifiable in the limit from positive data by Yokomori, but it is yet unknown whether there exists a characteristic sample of polynomial size for any very simple language.

In recent years, a horizontal table with a large number of attributes is widely used in OLAP or e-business applications to analyze multidimensional data efficiently. For efficient storing and querying of horizontal tables, recent works have tried to transform a horizontal table to a traditional vertical table. Existing works, however, have the drawback of not considering an optimized PIVOT operation provided (or to be provided) in recent commercial RDBMSs. In this paper we propose a formal approach that exploits the optimized PIVOT operation of commercial RDBMSs for storing and querying of horizontal tables. To achieve this goal, we first provide an overall framework that stores and queries a horizontal table using an equivalent vertical table. Under the proposed framework, we then formally define 1) a method that stores a horizontal table in an equivalent vertical table and 2) a PIVOT operation that converts a stored vertical table to an equivalent horizontal view. Next, we propose a novel method that transforms a user-specified query on horizontal tables to an equivalent PIVOT-included query on vertical tables. In particular, by providing transformation rules for all five elementary operations in relational algebra as theorems, we prove our method is theoretically applicable to commercial RDBMSs. Experimental results show that, compared with the earlier work, our method reduces storage space significantly and also improves average performance by several orders of magnitude. These results indicate that our method provides an excellent framework to maximize performance in handling horizontal tables by exploiting the optimized PIVOT operation in commercial RDBMSs.

The surface amino groups of plasma-polymerized films prepared from various nitrogen-containing monomers were quantitatively characterized for bioelectronic and biomedical applications. X-ray photoelectron spectroscopy (XPS) measurements were conducted on two kinds of surfaces: pristine surfaces of plasma-polymerized film prepared using various nitrogen-containing monomers, and theirs surfaces whose amino groups had been derivatized by a primary-amine-selective reagent carrying an XPS label. The XPS data showed that the maximum surface density of amino groups for this film was 8.41013 cm-2. Amino groups constituted 14-64% of all surface nitrogen atoms (NH/N), depending on the monomer used.

A framework for generating facial expressions from emotional states in daily conversation is described. It provides a mapping between emotional states and facial expressions, where the former is represented by vectors with psychologically-defined abstract dimensions, and the latter is coded by the Facial Action Coding System. In order to obtain the mapping, parallel data with rated emotional states and facial expressions were collected for utterances of a female speaker, and a neural network was trained with the data. The effectiveness of proposed method is verified by a subjective evaluation test. As the result, the Mean Opinion Score with respect to the suitability of generated facial expression was 3.86 for the speaker, which was close to that of hand-made facial expressions.

Today, localization of nodes in Wireless Sensor Networks (WSNs) is a challenging problem. Especially, it is almost impossible to guarantee that one algorithm giving optimal results for one topology will give optimal results for any other random topology. In this study, we propose a centralized, range- and anchor-based, hybrid algorithm called RH+ that aims to combine the powerful features of two orthogonal techniques: Classical Multi-Dimensional Scaling (CMDS) and Particle Spring Optimization (PSO). As a result, we find that our hybrid approach gives a fast-converging solution which is resilient to range-errors and very robust to topology changes. Across all topologies we studied, the average estimation error is less than 0.5 m. when the average node density is 10 and only 2.5% of the nodes are beacons.

Millimeter-waves integrated circuits offer a unique opportunity for a holistic design approach encompassing RF, analog, and digital, as well as radiation and electromagnetics. The ability to deal with the complete system covering a broad range from the digital circuitry to on-chip antennas and everything in between offers unparalleled opportunities for completely new architectures and topologies, which were previously impossible due the traditional partitioning of various blocks in conventional design. This can open a plethora of new architectural and system level innovation within the integrated circuit platform. This paper reviews some of the challenges and opportunities for mm-wave ICs and presents several solutions to them.

We propose a new algorithm for the blind source separation (BSS) approach in which independent component analysis (ICA) and frequency subband beamforming interpolation are combined. The slow convergence of the optimization of the separation filters is a problem in ICA. Our approach to resolving this problem is based on the relationship between ICA and null beamforming (NBF). The proposed method consists of the following three parts: (I) a frequency subband selector part for learning ICA, (II) a frequency domain ICA part with direction-of-arrivals (DOA) estimation of sound sources, and (III) an interpolation part in which null beamforming constructed with the estimated DOA is used. The results of the signal separation experiments under a reverberant condition reveal that the convergence speed is superior to that of the conventional ICA-based BSS methods.

A low distortion and low noise differential amplifier using the difference between the even- and odd-mode impedances is proposed. In order to realize an amplifier with high OIP3 and low NF characteristics, the impedance of the bias circuit should be low (<300 Ω) at the difference frequency and high (>4 kΩ) at the carrier frequency. Although the frequency response of the bias circuit impedance can only meet these conditions with difficulty, owing to the 20 MHz Tx signal bandwidth for 3G LTE, the proposed amplifier can achieve the impedance difference using the properties of a differential configuration where the difference frequency signal is the even-mode and the carrier frequency is the odd-mode. It has been demonstrated that the NF of the proposed amplifier, which has been fabricated in 0.18 µm SiGe BiCMOS technology operating at 2.14 GHz, can be kept to 1.6 dB or less and an OIP3 of 9.0 dBm can be achieved, which is 3 dB higher than that of a conventional amplifier, in the condition where the power gain is greater than 18 dB.

To improve the computation efficiency of the application specific instruction-set processor (ASIP), a strategy of hardware/software collaborative design is usually utilized. In this process, the auto-customization of specific instruction set has always been a key part to support the automated design of ASIP. The key issue of this problem is how to effectively reduce the huge exponential exploration space in the instruction identification process. To address this issue, we first formulate it as a feasible sub-graph enumeration problem under multiple constraints, and then propose a fast instruction identification algorithm based on a new model called basic convex pattern (BCP). The kernel technique in this algorithm is the transformation from the graph exploration to the formula-based computations. The experimental results have indicated that the proposed algorithm has a distinct reduction in the execution time.

In this paper, we propose a computationally efficient method of compensating temperature for the transaural stereo. The conventional method can be used to estimate the change in impulse responses caused by the fluctuation of temperature with high accuracy. However, the large amount of computation required makes real-time implementation difficult. Focusing on the fact that the amount of compensation depends on the length of the impulse response, we reduce the computation required by segmenting the impulse response. We segment the impulse responses in the time domain and estimate the effect of temperature fluctuation for each of the segments. By joining the processed segments, we obtain the compensated impulse response of the whole length. Experimental results show that the proposed method can reduce the computation required by a factor of nine without degradation of the accuracy.

A statistical model based on a partitioned Markov-chains model has previously been developed to represent time domain behavior of the asynchronous impulsive noise over a broadband power line communication (PLC) network. However, the estimation of its model parameters using the Simplex method can easily trap the final solution at a local optimum. This study proposes an estimation scheme based on the genetic algorithm (GA) to overcome this difficulty. Experimental results show that the proposed scheme yields estimates that more closely match the experimental data statistics.

A motion blur identification scheme is proposed for non-linear uniform motion blurs approximated by piecewise linear models which consist of more than one linear motion component. The proposed scheme includes three modules that are a motion direction estimator, a motion length estimator and a motion combination selector. In order to identify the motion directions, the proposed scheme is based on a trial restoration by using directional forward ramp motion blurs along different directions and an analysis of directional information via frequency domain by using a Radon transform. Autocorrelation functions of image derivatives along several directions are employed for estimation of the motion lengths. A proper motion combination is identified by analyzing local autocorrelation functions of non-flat component of trial restored results. Experimental examples of simulated and real world blurred images are given to demonstrate a promising performance of the proposed scheme.

A site-general type prediction formula is created based on the measurement results in an urban area in Japan assuming that the prediction frequency range required for Fourth -- Generation (4G) Mobile Communication Systems is from 3 to 6 GHz, the distance range is 0.1 to 3 km, and the base station (BS) height range is from 10 to 100 m. Based on the measurement results, the path loss (dB) is found to be proportional to the logarithm of the distance (m), the logarithm of the BS height (m), and the logarithm of the frequency (GHz). Furthermore, we examine the extension of existing formulae such as the Okumura -- Hata, Walfisch -- Ikegami, and Sakagami formulae for 4G systems and propose a prediction formula based on the Extended Sakagami formula.