This paper represents a low noise second harmonic oscillator using mutually synchronized Gunn diodes. A multi-layer MIC technology is adopted to reduce the circuit size of the oscillator. The oscillator consists of Gunn diodes, slot line resonators and strip lines. By embedding Gunn diodes in the slot line resonators, a harmonic RF signal can be generated very easily. The strip lines are used for the power combining output circuit. The shape of slot line resonator is square in order to achieve the low phase noise and the suppression of undesired harmonics. The second harmonic oscillator is designed and fabricated in K band. The output power is +8.89 dBm at the design frequency of 18.75 GHz (2f0) with the phase noise of -116.2 dBc/Hz at the offset frequency of 1 MHz. Excellent suppression of the undesired fundamental frequency signal (f0) of -33 dBc is achieved. Also, the circuit size is reduced by three-tenths relative to that of the previously proposed circuit.

The aim of this research is to study the power energy cost reduction of the mobile telecom industry through the supervisor control and data acquisition (SCADA) system application during globalization and liberalization competition. Yet this management system can be proposed functions: operating monitors, the analysis on load characteristics and dropping the cost of management.

We describe a user scheduling scheme suitable for zero-forcing beamforming (ZFBF) downlink multiuser multiple-input multiple-output (MU-MIMO) orthogonal frequency-division multiplexing (OFDM) transmissions in time-division-duplex distributed antenna systems. This user scheduling scheme consists of inter-cell-interference mitigation scheduling by using fractional frequency reuse, proportional fair scheduling in the OFDM frequency domain, and high-capacity ZFBF-MU-MIMO scheduling by using zero-forcing with selection (ZFS). Simulation results demonstrate in a severe user-distribution condition that includes cell-edge users that the proposed user scheduling scheme achieves high average cell throughputs close to that provided by only ZFS and that it also achieves almost the same degree of user fairness as round-robin user scheduling.

In a closed-loop scenario, the performance of transmit-diversity schemes for a multiple antenna system depends on the reliability of the channel state information (CSI). However, estimating the reliability of the instantaneous CSI at the transmitter is a challenging task. In this paper, we propose a robust transmit-diversity scheme for the case when the instantaneous CSI available at the transmitter is imperfect and its reliability is unknown to the transmitter. We show by simulation that our proposed scheme is efficient when the CSI reliability varies arbitrarily in every channel realization.

We present a new discriminative method of acoustic model adaptation that deals with a task-dependent speech variability. We have focused on differences of expressions or speaking styles between tasks and set the objective of this method as improving the recognition accuracy of indistinctly pronounced phrases dependent on a speaking style. The adaptation appends subword models for frequently observable variants of subwords in the task. To find the task-dependent variants, low-confidence words are statistically selected from words with higher frequency in the task's adaptation data by using their word lattices. HMM parameters of subword models dependent on the words are discriminatively trained by using linear transforms with a minimum phoneme error (MPE) criterion. For the MPE training, subword accuracy discriminating between the variants and the originals is also investigated. In speech recognition experiments, the proposed adaptation with the subword variants reduced the word error rate by 12.0% relative in a Japanese conversational broadcast task.

This paper presents a commercial shot classification scheme combining well-designed visual and textual features to automatically detect TV commercials. To identify the inherent difference between commercials and general programs, a special mid-level textual descriptor is proposed, aiming to capture the spatio-temporal properties of the video texts typical of commercials. In addition, we introduce an ensemble-learning based combination method, named Co-AdaBoost, to interactively exploit the intrinsic relations between the visual and textual features employed.

In this paper, we study an opportunistic scheduling scheme for the TDMA wireless network with relay stations. We model the time-varying channel condition of a wireless link as a stochastic process. Based on this model, we formulate an optimization problem for the opportunistic scheduling scheme that maximizes the expected system throughput while satisfying the QoS constraint of each user. In the opportunistic scheduling scheme for the system without relay stations, each user has only one communication path between the base station and itself, and thus only user selection is considered. However, in our opportunistic scheduling scheme for the system with relay stations, since there may exist multiple paths between the base station and a user, not only user selection but also path selection for the scheduled user is considered. In addition, we also propose an opportunistic time-sharing method for time-slot sharing between base station and relay stations. With the opportunistic time-sharing method, our opportunistic scheduling provides opportunistic resource sharing in three places in the system: user selection in a time-slot, path selection for the selected user, and time-slot sharing between base station and relay stations. Simulation results show that as the number of places that opportunistic resource sharing is applied to increases, the performance improvement also increases.

This paper tries to solve open Job-Shop Scheduling Problems (JSSP) by translating them into Boolean Satisfiability Testing Problems (SAT). The encoding method is essentially the same as the one proposed by Crawford and Baker. The open problems are ABZ8, ABZ9, YN1, YN2, YN3, and YN4. We proved that the best known upper bounds 678 of ABZ9 and 884 of YN1 are indeed optimal. We also improved the upper bound of YN2 and lower bounds of ABZ8, YN2, YN3 and YN4.

A low-voltage class-AB CMOS output stage with a tunable quiescent current control circuit is presented. It is based on a complementary common source. The quiescent current is detected by a compact circuit and can be adjusted by means of a control current without need to modify the transistor dimensions. The minimum supply voltage can be down to one threshold voltage plus two saturation voltages. It is suitable to drive low resistive loads. Simulation results are provided that are in agreement with expected characteristics.

In this paper, a cost-efficient LDPC decoder for DVB-S2 is presented. Based on the Normalized Min-Sum algorithm and the turbo-decoding message-passing (TDMP) algorithm, a dual line-scan scheduling is proposed to enable hardware reusing. Furthermore, we present the solution to the address conflict issue caused by the characteristic of the parity-check matrix defined by DVB-S2 LDPC codes. Based on SMIC 0.13 µm standard CMOS process, the LDPC decoder has an area of 12.51 mm2. The required operating frequency to meet the throughput requirement of 135 Mbps with maximum iteration number of 30 is 105 MHz. Compared with the latest published DVB-S2 LDPC decoder, the proposed decoder reduces area cost by 34%.

Maido-1 satellite was launched on 23 January 2009. The satellite carries the radio-frequency payload, Broadband Measurement of Waveform for VHF Lightning Impulses (VHF sensor), for research on lightning discharges. The final goal of our research is to locate sources of impulsive VHF radiation from lightning discharges and constantly monitor lightning activity from space. Maido-1 satellite has the aim of proving the functions of the sensor in space and to study the radio propagation characteristics of the ionosphere. Through the operation/observation for 5 months, more than 10,000 VHF signals have been recorded. The locations where VHF signals are detected and the examples of the received waveforms are presented in this paper. We discuss the regional dependency of the received signals.

This paper presents an efficient instruction scheduling algorithm which generates low-power codes for embedded system applications. Reordering and recoding are concurrently applied for low-power code generation in the proposed algorithm. By appropriate reordering of instruction sequences, the efficiency of instruction recoding is increased. The proposed algorithm constructs program codes on a basic-block basis by selecting a code sequence from among the schedules generated randomly and maintained by the system. By generating random schedules for each of the basic blocks constituting an application program, the proposed algorithm constructs a histogram graph for each of the instruction fields to estimate the figure-of-merits achievable by reordering instruction sequences. For further optimization, the system performs simulated annealing on the generated code. Experimental results for benchmark programs show that the codes generated by the proposed algorithm consume 37.2% less power on average when compared to the previous algorithm which performs list scheduling prior to instruction recoding.

Scanning quantized transform coefficients is an important tool for video coding. For example, the MPEG-4 video coder adopts three different scans to get better coding efficiency. This paper proposes an adaptive zero-coefficient distribution scan in inter block coding. The proposed method attempts to improve H.264/AVC zero coefficient coding by modifying the scan operation. Since the zero-coefficient distribution is changed by the proposed scan method, new VLC tables for syntax elements used in context-adaptive variable length coding (CAVLC) are also provided. The savings in bit-rate range from 2.2% to 5.1% in the high bit-rate cases, depending on different test sequences.

The proposed automated scoring system for English writing tests provides an assessment result including a score and diagnostic feedback to test-takers without human's efforts. The system analyzes an input sentence and detects errors related to spelling, syntax and content similarity. The scoring model has adopted one of the statistical approaches, a regression tree. A scoring model in general calculates a score based on the count and the types of automatically detected errors. Accordingly, a system with higher accuracy in detecting errors raises the accuracy in scoring a test. The accuracy of the system, however, cannot be fully guaranteed for several reasons, such as parsing failure, incompleteness of knowledge bases, and ambiguous nature of natural language. In this paper, we introduce an error-weighting technique, which is similar to term-weighting widely used in information retrieval. The error-weighting technique is applied to judge reliability of the errors detected by the system. The score calculated with the technique is proven to be more accurate than the score without it.

A good abdominal probabilistic atlas can provide important information to guide segmentation and registration applications in the abdomen. Here we build and test probabilistic atlases using 24 abdominal CT scans with available expert manual segmentations. Atlases are built by picking a target and mapping other training scans onto that target and then summing the results into one probabilistic atlas. We improve our previous abdominal atlas by 1) choosing a least biased target as determined by a statistical tool, i.e. multidimensional scaling operating on bending energy, 2) using a better set of control points to model the deformation, and 3) using higher information content CT scans with visible internal liver structures. One atlas is built in the least biased target space and two atlases are built in other target spaces for performance comparisons. The value of an atlas is assessed based on the resulting segmentations; whichever atlas yields the best segmentation performance is considered the better atlas. We consider two segmentation methods of abdominal volumes after registration with the probabilistic atlas: 1) simple segmentation by atlas thresholding and 2) application of a Bayesian maximum a posteriori method. Using jackknifing we measure the atlas-augmented segmentation performance with respect to manual expert segmentation and show that the atlas built in the least biased target space yields better segmentation performance than atlases built in other target spaces.

A third order harmonic oscillator has been proposed based on the resonant tunneling diode pair oscillators. This oscillator has significant advantages, good stability of the oscillation frequency against the load impedance change together with capability to output higher frequencies. Proper circuit operation has been demonstrated using circuit simulations. It has been also shown that the output frequency is stable against the load impedance change.

A digital spiking neuron is a wired system of shift registers that can generate spike-trains having various spike patterns by adjusting the wiring pattern between the registers. Inspired by the ultra-wideband impulse radio, a novel theoretical synthesis method of the neuron for application to spike-pattern division multiplex communications in an artificial pulse-coupled neural network is presented. Also, a novel heuristic learning algorithm of the neuron for realization of better communication performances is presented. In addition, fundamental comparisons to existing impulse radio sequence design methods are given.

The robust reduced order observer for a class of discrete-time Lipschitz nonlinear systems with external disturbance is proposed. It is shown that the proposed observer design can suppress the effect on the estimation error of external disturbance up to the prescribed level. Also, linear matrix inequalities are used to represent sufficient conditions on the existence of the proposed observer. Moreover, the maximum admissible Lipschitz constant of the proposed design is obtained for a given disturbance attenuation level. Finally, an illustrative example is given to verify the effectiveness of the proposed design.

E-band low-noise amplifier (LNA) monolithic millimeter-wave integrated circuits (MMICs) were developed using pseudomorphic In0.75Ga0.25As/In0.52Al0.48As high electron mobility transistors (HEMTs) with a gate length of 50 nm. The nanogate HEMTs demonstrated a maximum oscillation frequency (fmax) of 550 GHz and a current-gain cutoff frequency (fT) of 450 GHz at room temperature, which is first experimental demonstration that fmax as high as 550 GHz are achievable with the improved one-step-recessed gate procedure. Furthermore, using a three-stage LNA-MMIC with 50-nm-gate InGaAs/InAlAs HEMTs, we achieved a minimum noise figure of 2.3 dB with an associated gain of 20.6 dB at 79 GHz.

A method has been developed for deriving the approximate global optimum of a nonlinear objective function. First, the objective function is expanded into a linear equation for a moment vector, and the optimization problem is reduced to an eigen analysis problem in the wave coefficient space. Next, the process of the optimization is expressed using a Schrodinger-type equation, so global optimization is equivalent to eigen analysis of the Hamiltonian of a Schrodinger-type equation. Computer simulation of this method demonstrated that it produces a good approximation of the global optimum. An example optimization problem was solved using a Hamiltonian constructed by combining Hamiltonians for other optimization problems, demonstrating that various types of applications can be solved by combining simple Hamiltonians.