In this paper, we present an efficient downlink power control scheme, for wireless networks, based on two key ideas: (i) global-local fixed-point-approximation technique (GLOFPAT) and (ii) bottleneck removal criterion (BRC). The proposed scheme copes with all scenarios including infeasible case where no power allocation can provide all multiple accessing users with target quality of service (QoS). For feasible case, the GLOFPAT efficiently computes a desired power allocation which corresponds to the allocation achieved by conventional algorithms. For infeasible case, the GLOFPAT offers valuable information to detect bottleneck users, to be removed based on the BRC, which deteriorate overall QoS. The GLOFPAT is a mathematically-sound distributed algorithm approximating desired power allocation as a unique fixed-point of an isotone mapping. The unique fixed-point of the global mapping is iteratively computed by fixed-point-approximations of multiple distributed local mappings, which can be computed in parallel by base stations respectively. For proper detection of bottleneck users, complete analysis of the GLOFPAT is presented with aid of the Tarski's fixed-point theorem. Extensive simulations demonstrate that the proposed scheme converges faster than the conventional algorithm and successfully increases the number of happy users receiving target QoS.

We have developed an optical connector assembly method that allows the rapid on-site installation of an optical connector. To simplify this on-site assembly process we fabricated built-in parts that enable us to install the optical connector using pre-assembled optical connector parts. Moreover, we have established an advanced method for applying a solidifying agent that adheres to the inner wall of a ferrule flange. With our assembly method, we can complete on-site optical connector installation, other than the polishing process, in two steps, namely bonding agent application and fiber insertion.

A multi-stage approach -- which is fast, robust and easy to train -- for a face-detection system is proposed. Motivated by the work of Viola and Jones [1], this approach uses a cascade of classifiers to yield a coarse-to-fine strategy to reduce significantly detection time while maintaining a high detection rate. However, it is distinguished from previous work by two features. First, a new stage has been added to detect face candidate regions more quickly by using a larger window size and larger moving step size. Second, support vector machine (SVM) classifiers are used instead of AdaBoost classifiers in the last stage, and Haar wavelet features selected by the previous stage are reused for the SVM classifiers robustly and efficiently. By combining AdaBoost and SVM classifiers, the final system can achieve both fast and robust detection because most non-face patterns are rejected quickly in earlier layers, while only a small number of promising face patterns are classified robustly in later layers. The proposed multi-stage-based system has been shown to run faster than the original AdaBoost-based system while maintaining comparable accuracy.

In this paper, we report a manufacturable InP DHBT technology, suitable for medium scale mixed-signal and monolithic microwave integrated circuits. The InGaAs/InP DHBTs were grown by MBE and fabricated using conventional process techniques. Devices with an emitter junction area of 4.8 µm2 exhibited peak cutoff frequency (fT) and maximum oscillation frequency (fMAX) values of 265 and 305 GHz, respectively, and a breakdown voltage (BVCEo) of over 5 V. Using this technology, a set of mixed-signal IC building blocks for ≥ 80 Gbit/s fibre optical links, including distributed amplifiers (DA), voltage controlled oscillators (VCO), and multiplexers (MUX), have been successfully fabricated and operated at 80 Gbit/s and beyond.

Pt Schottky diode gas sensors for carbon monoxide (CO) were fabricated using slightly Si doped bulk GaN grown on sapphire substrate. The influence of diode size, Pt thickness, operating temperature on gas sensitivity was investigated. CO sensitivity was improved six times by optimizing the size and thickness of the Pt contact. Surface restructuring and morphology changes of Pt film were observed after thermal annealing. These changes are enhanced as the film thickness is reduced further and contribute to improve CO sensitivity.

Experimental result and theoretical analysis are reported for bias-voltage dependence of oscillation frequency in resonant tunneling diodes (RTDs) integrated with slot antennas. Frequency change of 18 GHz is obtained experimentally for a device with the central oscillation frequency of 470 GHz. The observed frequency change is attributed to the bias-voltage dependence of the transit time of electrons across the RTD layers, which results in a voltage-dependent capacitance added to RTD. Theoretical analysis taking into account this transit time is in reasonable agreement with the observed results. Voltage-controlled RTD oscillators in the terahertz range are expected from the theoretical results. A structure suitable for large frequency change is also discussed briefly.

In this paper, we present laboratory and field experimental results using High Speed Downlink Packet Access (HSDPA) test-beds in order to reveal the actual HSDPA performance based on key technologies such as base station (BS) scheduling, adaptive modulation and coding, hybrid automatic repeat request, and advanced receiver design. First, this paper evaluates the effects of advanced user equipment capabilities such as the maximum number of multi-codes, transmit diversity, receive diversity, and a chip equalizer. Increases in throughput of 60% and 85% due to using 10 and 15 codes were observed compared to 5 codes, respectively. The gain of 22% was obtained by applying closed-loop transmit diversity to the HSDPA network. Receive diversity improves the throughput in the region from low to high signal-to-interference ratio, and the gain of 45% was obtained by applying receive diversity to the conventional RAKE receiver. A throughput gain of approximately 17% due to the use of the chip equalizer was obtained and it was observed mainly in the high Ior/Ioc region and under multi-path conditions. Second, field experiments are conducted to elucidate the effects of multi-user diversity using a BS scheduling algorithm, and reveal that proportional fairness scheduling provides both the increase in sector throughput of 18% and a sufficient degree of fairness among users. The transmit control protocol (TCP)-level throughput performance is also investigated in order to reveal the actual end-user throughput. The results show that the throughput rate of approximately 90% of the throughput of the MAC-hs layer is achieved in the TCP layer in the laboratory experiments and in the field experiments.

In this letter, we study the problem of designing an efficient power and bit allocation scheme in the context of a hierarchical image transmission system based on an embedded multi-carrier modulation (EMCM) scheme over digital subscriber line. Authors describe a novel algorithm that performs power minimization under bit rate constraint and QoS requirement. It is based on the Hughes-Hartogs algorithm, and successively allocates the bits of the high, then low priority data streams. Simulations that assess the performance of the proposed algorithm are also provided and discussed; they demonstrate the interest of the proposed scheme.

This paper presents a view independent video-based face recognition method using posterior probability in Kernel Fisher Discriminant (KFD) space. In practical environment, the view of faces changes dynamically. Robustness to view changes is required for video-based face recognition in practical environment. Since the view changes induce large non-linear variation, kernel-based methods are appropriate. We use KFD analysis to cope with non-linear variation. To classify image sequence, the posterior probability in KFD space is used. KFD analysis assumes that the distribution of each class in high dimensional space is Gaussian. This makes the computation of posterior probability in KFD space easy. The combination of KFD space and posterior probability of image sequence is the main contribution of the proposed method. The performance is evaluated by using two face databases. Effectiveness of the proposed method is shown by the comparison with the other feature spaces and classification methods.

We developed a system that detects the vehicle driving immediately ahead of one's own car in the same lane and measures the distance to and relative speed of that vehicle to prevent accidents such as rear-end collisions. The system is the first in the industry to use non-scanning millimeter-wave radar combined with a sturdy stereo image sensor, which keeps cost low. It can operate stably in adverse weather conditions such as rain, which could not easily be done with previous sensors. The system's vehicle detection performance was tested, and the system can correctly detect vehicles driving 3 to 50 m ahead in the same lane with higher than 99% accuracy in clear weather. Detection performance in rainy weather, where water drops and splashes notably degraded visibility, was higher than 90%.

Developing embedded parallel image processing applications is usually a very hardware-dependent process, often using the single instruction multiple data (SIMD) paradigm, and requiring deep knowledge of the processors used. Furthermore, the application is tailored to a specific hardware platform, and if the chosen hardware does not meet the requirements, it must be rewritten for a new platform. We have proposed the use of design space exploration [9] to find the most suitable hardware platform for a certain application. This requires a hardware-independent program, and we use algorithmic skeletons [5] to achieve this, while exploiting the data parallelism inherent to low-level image processing. However, since different operations run best on different kinds of processors, we need to exploit task parallelism as well. This paper describes how we exploit task parallelism using an asynchronous remote procedure call (RPC) system, optimized for low-memory and sparsely connected systems such as smart cameras. It uses a futures [16]-like model to present a normal imperative C-interface to the user in which the skeleton calls are implicitly parallelized and pipelined. Simulation provides the task dependency graph and performance numbers for the mapping, which can be done at run time to facilitate data dependent branching. The result is an easy to program, platform independent framework which shields the user from the parallel implementation and mapping of his application, while efficiently utilizing on-chip memory and interconnect bandwidth.

In this paper, we proposed a new Two-Dimensional Linear Discriminant Analysis (2DLDA) method, based on Two-Dimensional Principle Component Analysis (2DPCA) concept. In particular, 2D face image matrices do not need to be previously transformed into a vector. In this way, the spatial information can be preserved. Moreover, the 2DLDA also allows avoiding the Small Sample Size (SSS) problem, thus overcoming the traditional LDA. We combine 2DPCA and our proposed 2DLDA on the Two-Dimensional Linear Discriminant Analysis of principle component vectors framework. Our framework consists of two steps: first we project an input face image into the family of projected vectors via 2DPCA-based technique, second we project from these space into the classification space via 2DLDA-based technique. This does not only allows further reducing of the dimension of feature matrix but also improving the classification accuracy. Experimental results on ORL and Yale face database showed an improvement of 2DPCA-based technique over the conventional PCA technique.

This paper presents a 3D feature-based binocular tracking algorithm for tracking crowded people indoors. The algorithm consists of a two stage 3D feature points grouping method and a robust 3D feature-based tracking method. The two stage 3D feature points grouping method can use kernel-based ISODATA method to detect people accurately even though the part or almost full occlusion occurs among people in surveillance area. The robust 3D feature-based Tracking method combines interacting multiple model (IMM) method with a cascade multiple feature data association method. The robust 3D feature-based tracking method not only manages the generation and disappearance of a trajectory, but also can deal with the interaction of people and track people maneuvering. Experimental results demonstrate the robustness and efficiency of the proposed framework. It is real-time and not sensitive to the variable frame to frame interval time. It also can deal with the occlusion of people and do well in those cases that people rotate and wriggle.

A novel resonant tunneling diode (RTD) oscillator is proposed, which overcomes the problems of the conventional RTD oscillators, such as the low-frequency spurious oscillation and the bias instability. Our proposal consists of two RTDs connected serially, and the resonator connected to the node between two RTDs. This circuit separates the oscillation node from the bias nodes, and suppresses the above mentioned problems. This relaxes the severe restriction on the RTD area, and makes it possible to supply higher power to a load. Circuit simulation shows that with this circuit more than 2 mW power can be supplied to the 50 Ω resistive load at 100 GHz using RTDs having 105 A/cm2-peak current density and 20 µm2-area. It also shows that the dc-to-RF conversion efficiency is as good as that of conventional ones. Furthermore, we have studied the extension of this oscillator having 4 RTDs connected serially. Circuit simulations revealed that using this circuit the power can be doubled with a good conversion efficiency.

We study the coupled spatio-temporal variations of the electron density and the electric field (electron plasma oscillations) in high-electron mobility transistors using the developed device model. The excitation of electron plasma oscillations in the terahertz range of frequencies might lead to the emission of terahertz radiation. In the framework of the model developed, we calculate the resonant plasma frequencies and find the conditions for the plasma oscillations self-excitation (plasma instability) We show that the transit-time effect in the high-electric field region near the drain edge of the channel of high-electron mobility transistors can cause the self-excitation of the plasma oscillations. It is shown that the self-excitation of plasma oscillations is possible when the ratio of the electron velocity in the high field region, ud, and the gate length, Lg, i.e., the inverse transit time are sufficiently large in comparison with the electron collision frequency in the gated channel, ν. The transit-time mechanism of plasma instability under consideration can superimpose on the Dyakonov-Shur mechanism predicted previously strongly affecting the conditions of the instability and, hence, terahertz emission. The instability mechanism under consideration might shed light on the origin of terahertz emission from high electron mobility transistors observed in recent experiments.

Sensing elements based on AlGaN/GaN HEMT and Schottky diode structures have been investigated in relation with the strain sensitivity of their characteristics. Piezoresistance of the Al0.3Ga0.7N/GaN HEMT-channel as well as changes in the current-voltage characteristics of the Schottky diodes have been observed with gauge factor (GF) values ranging between 19 and 350 for the selected biasing conditions. While a stable response to strain was measured, the observed temperature dependence of the channel resistance demonstrates the need for a systematic characterisation of the sensor properties to allow compensation of the observed temperature effects.

Plasma oscillations in nanometer field effect transistors are used for detection and generation of electromagnetic radiation of THz frequency. Following first observations of resonant detection in 150 nm gate length GaAs HEMT, we describe recent observations of room temperature detection in nanometer Si MOSFETs, resonant detection in GaN/AlGaN HEMTs and improvement of room temperature detection in GaAs HEMTs due to the drain current. Experiments on spectrally resolved THz emission are described that involve room and liquid helium temperature emission from nanometer GaInAs and GaN HEMTs.

The EDD connection admission control scheme has been proposed for supporting real-time communication in packet-switched networks. In the scheme, when a connection establishment request occurs, the worst-case link delay in each link along the connection is calculated to determine whether the request can be accepted or not. In order to calculate the worst-case link delay, we must perform a check called the point schedulability check for each of some discrete time instants (checkpoints). Therefore when there are many checkpoints, the worst-case link delay calculation is time-consuming. We have proposed a high-speed calculation method. The method finds some checkpoints for which the point schedulability check need not be performed and removes such unnecessary checkpoints in advance before a connection establishment request occurs, and the check is performed for each of the remaining checkpoints after the request occurs. However, the method is not so effective under the situation that the maximum packet length in networks is large, because the method can find few unnecessary checkpoints under the situation. This paper proposes a new high-speed calculation method. We relax the condition which determines whether or not the point schedulability check need not be performed for each checkpoint in our previous method and derive a new condition for finding unnecessary checkpoints. Using the proposed method based on the new condition, we can increase the number of unnecessary checkpoints compared to our previous method. Numerical examples which are obtained by extensive simulation show that the proposed method can attain as much as about 50 times speedup.

The minimization problem of an L2-sensitivity measure subject to L2-norm dynamic-range scaling constraints is formulated for a class of two-dimensional (2-D) state-space digital filters. First, the problem is converted into an unconstrained optimization problem by using linear-algebraic techniques. Next, the unconstrained optimization problem is solved by applying an efficient quasi-Newton algorithm with closed-form formula for gradient evaluation. The coordinate transformation matrix obtained is then used to synthesize the optimal 2-D state-space filter structure that minimizes the L2-sensitivity measure subject to L2-norm dynamic-range scaling constraints. Finally, a numerical example is presented to illustrate the utility of the proposed technique.

This paper proposes a novel image processing method based on a percolation model. The percolation model is used to represent the natural phenomenon of the permeation of liquid. The percolation takes into account the connectivity among the neighborhoods. In the proposed method, a cluster formation by the percolation process is performed first. Then, feature extraction from the cluster is carried out. Therefore, this method is a type of scalable window processing for realizing a robust and flexible feature extraction. The effectiveness of proposed method was verified by experiments on crack detection, noise reduction, and edge detection.