The wideband noise controlling performance of the delayless subband adaptive filtering technique is affected by the group delay and in-band aliasing distortion of analysis filter banks. A method of recursive second-order cone programming is proposed to design the uniform DFT modulated analysis filter banks, with a small in-band aliasing error and low group delay. Simulation results show that the noise controlling performance is improved with small residual noise power spectra, a high noise attenuation level and fast convergence rate.

In this paper, we present an algorithm to segment the liver in low-contrast CT images. As the first step of our algorithm, we define a search range for the liver boundary. Then, the EM algorithm is utilized to estimate parameters of a 'Gaussian Mixture' model that conforms to the intensity distribution of the liver. Using the statistical parameters of the intensity distribution, we introduce a new thresholding technique to classify image pixels. We assign a distance feature vectors to each pixel and segment the liver by a K-means clustering scheme. This initial boundary of the liver is conditioned by the Fourier transform. Then, a Geodesic Active Contour algorithm uses the boundaries to find the final surface. The novelty in our method is the proper selection and combination of sub-algorithms so as to find the border of an object in a low-contrast image. The number of parameters in the proposed method is low and the parameters have a low range of variations. We applied our method to 30 datasets including normal and abnormal cases of low-contrast/high-contrast images and it was extensively evaluated both quantitatively and qualitatively. Minimum of Dice similarity measures of the results is 0.89. Assessment of the results proves the potential of the proposed method for segmentation in low-contrast images.

We present an Interactive Tabu Search (ITS) algorithm to reduce the evaluation load of Interactive Evolutionary Computation (IEC) users. Most previous IEC studies used an evaluation interface that required users to provide evaluation values for all candidate solutions. However, user's burden with such an evaluation interface is large. Therefore, we propose ITS where users choose the favorite candidate solution from the presented candidate solutions. Tabu Search (TS) is recognized as an optimization technique. ITS evaluation is simpler than Interactive Genetic Algorithm (IGA) evaluation, in which users provide evaluation values for all candidate solutions. Therefore, ITS is effective for reducing user evaluation load. We evaluated the performance of our proposed ITS and a Normal IGA (NIGA), which is a conventional 10-stage evaluation, using a numerical simulation with an evaluation agent that imitates human preferences (Kansei). In addition, we implemented an ITS evaluation for a running-shoes-design system and examined its effectiveness through an experiment with real users. The simulation results showed that the evolution performance of ITS is better than that of NIGA. In addition, we conducted an evaluation experiment with 21 subjects in their 20 s to assess the effectiveness of these methods. The results showed that the satisfaction levels for the candidates generated by ITS and NIGA were approximately equal. Moreover, it was easier for test subjects to evaluate candidate solutions with ITS than with NIGA.

In this paper, a hybrid parallel implementation of inverse matrix computation using SMW formula is proposed. By aggregating the memory bandwidth in the hybrid parallel implementation, the bottleneck due to the memory bandwidth limitation in the authors previous multicore implementation has been dissolved. More than 8 times of speed up is also achieved with dual-core 8-nodes implementation which leads more than 20 simulation steps per second, or near real-time performance.

A reverse mode liquid crystal (LC) display has been investigated. A driving voltage strongly depends on a morphology which changes by reactive mesogens, photo initiators and LCs. It becomes higher when the domain size of the liquid crystal and the particle of the polymer reactive mesogen are smaller.

In this paper, we propose an automatic parameter adjustment method for audio equalizers using an interactive genetic algorithm (IGA). It is very difficult for ordinary users who are not familiar with audio devices to appropriately adjust the parameters of audio equalizers. We therefore propose a system that can automatically adjust the parameters of audio equalizers on the basis of user's evaluation of the reproduced sound. The proposed system utilizes an IGA to adjust the gains and Q values of the peaking filters included in audio equalizers. Listening test results demonstrate that the proposed system can appropriately adjust the parameters on the basis of the user's evaluation.

We propose an active learning framework for speech recognition that reduces the amount of data required for acoustic modeling. This framework consists of two steps. We first obtain a phone-error distribution using an acoustic model estimated from transcribed speech data. Then, from a text corpus we select a sentence whose phone-occurrence distribution is close to the phone-error distribution and collect its speech data. We repeat this process to increase the amount of transcribed speech data. We applied this framework to speaker adaptation and acoustic model training. Our evaluation results showed that it significantly reduced the amount of transcribed data while maintaining the same level of accuracy.

The left-handed (LH) operation of a three-dimensional (3-D) LH material composed of wired metallic spheres is experimentally confirmed. A 15153-cell periodic structure designed to have an isotropic LH characteristics is fabricated by a 3-D printer with post plating technology, and near-field measurements of refracted waves by the negative refractive index slab lens are carried out. The dispersion characteristics measured from the near-field distributions on the surface of the LH material clearly show that the structure supports the backward waves at 12 GHz band. It is also shown experimentally that the resolution of the slab lens exceeds the diffraction limit by near field measurements with a single source and adjacent two sources. In addition, near-field measurements from the LH material near the Γ-point frequency at 12.90 GHz are carried out. A highly directive plane wave with a single point source is observed and the near-zero-index operation has been confirmed.

We investigate the impact of traffic on the performance of large-scale NAT (LSN), since it has been attracting attention as a means of better utilizing the limited number of global IPv4 addresses. We focus on the number of active flows because they drive up the LSN memory requirements in two ways; more flows must be held in LSN memory, and more global IPv4 addresses must be prepared. Through traffic measurement data analysis, we found that more than 1% of hosts generated more than 100 TCP flows or 486 UDP flows at the same time, and on average, there were 1.43-3.99 active TCP flows per host, when the inactive timer used to clear the flow state from a flow table was set to 15 s. When the timer is changed from 15 s to 10 min, the number of active flows increases more than tenfold. We also investigate how to reduce the above impact on LSN in terms of saving memory space and accommodating more users for each global IPv4 address. We show that to save memory space, regulating network anomalies can reduce the number of active TCP flows on an LSN by a maximum of 48.3% and by 29.6% on average. We also discuss the applicability of a batch flow-arrival model for estimating the variation in the number of active flows, when taking into account that the variation is needed to prepare an appropriate memory space. One way to allow each global IPv4 address to accommodate more users is to better utilize destination IP address information when mapping a source IP address from a private address to a global IPv4 address. This can effectively reduce the required number of global IPv4 addresses by 85.9% for TCP traffic and 91.9% for UDP traffic on average.

The objective of pool-based incremental active learning is to choose a sample to label from a pool of unlabeled samples in an incremental manner so that the generalization error is minimized. In this scenario, the generalization error often hits a minimum in the middle of the incremental active learning procedure and then it starts to increase. In this paper, we address the problem of early labeling stopping in probabilistic classification for minimizing the generalization error and the labeling cost. Among several possible strategies, we propose to stop labeling when the empirical class-posterior approximation error is maximized. Experiments on benchmark datasets demonstrate the usefulness of the proposed strategy.

In this paper, we present an automatic vision-based traffic sign recognition system, which can detect and classify traffic signs at long distance under different lighting conditions. To realize this purpose, the traffic sign recognition is developed in an originally proposed dual-focal active camera system. In this system, a telephoto camera is equipped as an assistant of a wide angle camera. The telephoto camera can capture a high accuracy image for an object of interest in the view field of the wide angle camera. The image from the telephoto camera provides enough information for recognition when the accuracy of traffic sign is low from the wide angle camera. In the proposed system, the traffic sign detection and classification are processed separately for different images from the wide angle camera and telephoto camera. Besides, in order to detect traffic sign from complex background in different lighting conditions, we propose a type of color transformation which is invariant to light changing. This color transformation is conducted to highlight the pattern of traffic signs by reducing the complexity of background. Based on the color transformation, a multi-resolution detector with cascade mode is trained and used to locate traffic signs at low resolution in the image from the wide angle camera. After detection, the system actively captures a high accuracy image of each detected traffic sign by controlling the direction and exposure time of the telephoto camera based on the information from the wide angle camera. Moreover, in classification, a hierarchical classifier is constructed and used to recognize the detected traffic signs in the high accuracy image from the telephoto camera. Finally, based on the proposed system, a set of experiments in the domain of traffic sign recognition is presented. The experimental results demonstrate that the proposed system can effectively recognize traffic signs at low resolution in different lighting conditions.

The authors propose a new method of controlling the isolation of an RF splitter. In the proposed method, a bias current is superimposed on an RF signal to change the permeability of the ferrite core used in the splitter's transformer. By doing this, the splitter isolation can be controlled. Experimental results have shown that superimposing a bias current of 500 mA improves device isolation by about 5 dB without affecting the loss characteristics.

In NGN standards, End Host, also referred to as Terminal Equipment (TE), holds an important place in end-to-end path performance. However, most researchers neglect TE performance when considering performance of end-to-end paths. As far as the authors' knowledge goes, no previous study has proposed a model for TE performance. This paper proposes a method for measuring performance of TE and model extraction based on measurement data. The measurement was made possible with the use of a special NPU (Network Processing Unit) implemented as a programmable NIC. Along with the probing itself, a framework for removing the skew between the NPU and OS is developed in this paper. The multidimensional analysis includes method of probing, packet size and background traffic volume, and studies their effect on TE performance. A method for extracting a generic TE model is proposed. The outcome of this research can be used for modelling TE in simulations and in modelling end-to-end performance when considering QoS in NGN.

An active learning method, called Two-stage Active learning algorithm (TAL), is developed for software defect prediction. Combining the clustering and support vector machine techniques, this method improves the performance of the predictor with less labeling effort. Experiments validate its effectiveness.

This paper presents analysis and design of a new ultra-low voltage analog front end (AFE) dedicated to strain sensor applications. The AFE, designed in 0.18 µm CMOS process, features a chopper-stabilized instrumentation amplifier (IA), a balanced active MOSFET-C 2nd order low pass filter (LPF), a clock generator and a voltage booster which operate at supply voltage (Vdd) of 0.6 V. The designed IA achieves 30 dB of closed-loop gain, 101 dB of common-mode rejection ratio (CMRR) at 50 Hz, 80 dB of power-supply rejection ratio (PSRR) at 50 Hz, thermal noise floor of 53.4 nV/, current consumption of 14 µA, and noise efficiency factor (NEF) of 9.7. The high CMRR and rail-to-rail output swing capability is attributed to a new low voltage realization of the active-bootstrapped technique using a pseudo-differential gain-boosting operational transconductance amplifier (OTA) and proposed current-driven bulk (CDB) biasing technique. An output capacitor-less low-dropout regulator (LDO), with a new fast start-up LPF technique, is used to regulate this 0.6 V supply from a 0.8–1.0 V energy harvesting power source. It achieves power supply rejection (PSR) of 42 dB at frequency of 1 MHz. A cascode compensated pseudo differential amplifier is used as the filter's building block for low power design. The filter's single-ended-to-balanced converter is implemented using a new low voltage amplifier with two-stage common-mode cancellation. The overall AFE was simulated to have 65.6 dB of signal-to-noise ratio (SNR), total harmonic distortion (THD) of less than 0.9% for a 100 Hz sinusoidal maximum input signal, bandwidth of 2 kHz, and power consumption of 51.2 µW. Spectre RF simulations were performed to validate the design using BSIM3V3 transistor models provided by GLOBALFOUNDRIES 0.18 µm CMOS process.

“Internet of Things” (IoT) requires information to be collected from “anything”, “anytime”, and “anywhere”. In order to achieve this, wireless devices are required that have (1) automatic data acquisition capability, (2) small size, (3) long life, and (4) long range communication capability. One way to meet these requirements is to adopt active Radio Frequency Identification (RFID) systems. Active RFID is more advantageous than passive RFID and enables higher data reading performance over longer distances. This paper surveys active RFID systems, the services they currently promise to provide, technical problems common to these services, and the direction in which research should head in the future. It also reports the results of EPCglobal (EPC: Electronic Product Code) pilot tests conducted on global logistics for tracking ocean/air container transportation using active RFID systems for which we developed several new types of active RFID tags. The test results confirm that our active RFID tags have sufficient capability and low power consumption to well support ocean/air transportation and logistics service.

This paper proposes a scalable active optical access network using high-speed Plumbum Lanthanum Zirconate Titanate (PLZT) optical switch/splitter. The Active Optical Network, called ActiON, using PLZT switching technology has been presented to increase the number of subscribers and the maximum transmission distance, compared to the Passive Optical Network (PON). ActiON supports the multicast slot allocation realized by running the PLZT switch elements in the splitter mode, which forces the switch to behave as an optical splitter. However, the previous ActiON creates a tradeoff between the network scalability and the power loss experienced by the optical signal to each user. It does not use the optical power efficiently because the optical power is simply divided into 0.5 to 0.5 without considering transmission distance from OLT to each ONU. The proposed network adopts PLZT switch elements in the variable splitter mode, which controls the split ratio of the optical power considering the transmission distance from OLT to each ONU, in addition to PLZT switch elements in existing two modes, the switching mode and the splitter mode. The proposed network introduces the flexible multicast slot allocation according to the transmission distance from OLT to each user and the number of required users using three modes, while keeping the advantages of ActiON, which are to support scalable and secure access services. Numerical results show that the proposed network dramatically reduces the required number of slots and supports high bandwidth efficiency services and extends the coverage of access network, compared to the previous ActiON, and the required computation time for selecting multicast users is less than 30 msec, which is acceptable for on-demand broadcast services.

We investigated optical transmission characteristics of aluminum thin films with periodic hole arrays in sub-wavelength. We divided white light into several color spectra using a color filter based on the surface plasmon resonance (SPR) utilizing aluminum showing high plasma frequency. By optimizing a hole-array period, hole shape, polarization and index difference of two surface, transmittance of 30% and full-width at half-maximum of around 100 nm were achieved.

An anonymous credential system enables individuals to selectively prove their attributes while all other knowledge remains hidden. We considered the applicability of such a system to large scale infrastructure systems and perceived that revocations are still a problem. Then we contrived a scenario to lessen the number of revocations by using more attributes. In this scenario, each individual needs to handle a huge number of attributes, which is not practical with conventional systems. In particular, each individual needs to prove small amounts of attributes among a huge number of attributes and the manager of the system needs to certify a huge number of attributes of individuals periodically. These processes consume extremely large resources. This paper proposes an anonymous credential system in which both a user's proving attributes set, which is included in a huge attribute set, and manager's certifying attributes are very efficient. Conclusion Our proposal enables an anonymous credential system to be deployed as a large scale infrastructure system.

An inductorless low noise amplifier (LNA) with active balun for digital TV (DTV) applications is presented. The LNA exploits a noise cancellation technique which allows for simultaneous wide-band impedance matching and low noise design. The matching and amplifier stages in the LNA topology perform single-ended to differential signal conversion with balanced output. The second and third-order nonlinearity of the individual amplifiers as well as the distortion caused by the interaction between the stages are suppressed to achieve high IIP2 and IIP3. A method for intrinsic cancellation of the second-order interaction is employed to reduce the dependence of the IIP3 on the frequency spacing between the interfering signals in the two-tone test of DTV tuners. Fabricated in a 0.18 µm CMOS technology, the LNA core size is 0.21 mm2. Measurements show that the LNA IIP3 and IIP2 are +12 dBm and +21 dBm, respectively. The IIP3 variation is less than 5 dB in the 10 MHz to 200 MHz frequency spacing range. A voltage gain of 14.5 dB and a noise figure below 4 dB are achieved in a frequency range from 100 MHz to 1 GHz. The LNA consumes 11 mA from a 1.8 V supply voltage.