In this paper, we propose a novel incremental method for discovering latent variables from multivariate data with high efficiency. It integrates non-Gaussianity and an adaptive incremental model in an unsupervised way to extract informative features. Our proposed method discovers a small number of compact features from a very large number of features and can still achieve good predictive performance in EEG signals. The promising EEG signal classification results from our experiments prove that this approach can successfully extract important features. Our proposed method also has low memory requirements and computational costs.

An equivalent network analysis for an arrangement that combines a microstrip line and coaxial conductor for the purpose of measuring permeability is discussed in this paper. The measurement circuit used consists of a coaxial conductor with a sample housed inside and a short microstrip line connected to both sides. The coaxial conductor is composed of an electrically grounded coaxial metal pipe with open ends and a center conductor. Equivalent networks for this arrangement are investigated to determine the complex permeability from the impedance of the measurement circuit. We have employed a π network composed of a resistor and an inductor connected in series, and shunt capacitors as the equivalent circuit for the measurement portion. It has been found that the measurement error ratio of less than a few percent can be obtained for most frequency ranges of 10 MHz to 500 MHz.

In this paper, impulse noise removal for digital images is handled. It is well-known that switching-type processing is effective for the impulse noise removal. In the process, noise-corrupted pixels are first detected, and then, filtering is applied to the detected pixels. This switching process prevents distorting original signals. A noise detector is of course important in the process, a filter for pixel value restoration is also important to obtain excellent results. The authors have proposed a local similarity-based filter (LSF). It utilizes local similarity in a digital image and its capability against restoration of orderly regions has shown in the previous paper. In this paper, first, further experiments are carried out and properties of the LSF are revealed. Although LSF is inferior to an existing filter when disorderly regions are processed and evaluated by the peak signal-to-noise ratio, its outputs are subjectively adequate even in the case. If noise positions are correctly detected, capability of the LSF is guaranteed. On the other hand, some errors may occur in actual noise detection. In that case, LSF sometimes fails to restoration. After properties are examined, we propose two effective extensions to the LSF. First one is for computational cost reduction and another is for color image processing. The original LSF is very time consuming, and in this paper, computational cost reduction is realized introducing a search area. Second proposal is the vector LSF (VLSF) for color images. Although color images can be processed using a filter, which is for monochrome images, to each color component, it sometimes causes color drift. Hence vector processing has been investigated so far. However, existing vector filters do not excel in preservation of orderly pattern although color drift is suppressed. Our proposed VLSF is superior both in orderly pattern preservation and color drift suppression. Effectiveness of the proposed extensions to LSF is verified through experiments.

An instrument that can efficiently measure individual competency of IT applications (ICITA) is presented. It allows an organization to develop and manage the IT application capability of individuals working in an enterprise IT environment. The measurement items are generated from the definition and major components of individual competency of IT applications. The reliability and validity of the instrument construct are verified by factor and correlation analysis. A 15-item instrument is proposed to efficiently measure individual competency of IT applications and the instrument will contribute to the improved ICITA of human resources working in an enterprise IT environment.

A can swells due to gas produced from an inner food caused by poor hermetic sealing of the can. This paper presents a measurement for the bottom shape to detect a swelled can by using the millimeter-wave imaging. For get higher spatial resolution and an adjustable focal distance, two collimated beam lenses were applied to the measurement system. First, a configuration of the system was studied with the electrical field intensity and focal distance by using full wave electromagnetic simulation. Next, the bottom shapes of cans with different pressure were evaluated quantitatively using the system. A shape change of 0.5 mm was detected with pressure difference of 50 kPa, and it is reasonable considering actual dimension of the can shape. A potential of the proposed detection method was presented.

This paper investigates the use of cooperative spectrum sensing (CSS) to detect primary user (PU) signals during spectrum sharing between the PU and the secondary user (SU). In particular, we employ a variant of CSS (which achieves space diversity), called weighted gain combining CSS (W-CSS), which has the potential to achieve increased diversity gain and enhance detection performance. In a typical W-CSS system, the SU needs to obtain the PU signal power information in order to set the proper weight value. However, as it is hard for the SU to ascertain whether the PU is present or absent, this is difficult to obtain. To address this problem, a PU signal power estimation algorithm is introduced. In addition, we also analyze the statistics of the estimator and derive the detection probability of the W-CSS when the PU signal power estimation algorithm is applied. The analysis and related simulation results reveal that the detection probability of the proposed W-CSS under time-variant Rayleigh fading asymptotically approaches the detection probability in an additive white Gaussian noise channel as the number of antennas is increased. This also follows results from our Monte Carlo simulations, showing that multiple antenna elements could suppress the effect of Rayleigh fading. In short, the accuracy of the estimation algorithm is affected by channel variation (especially in the case of fast Rayleigh fading). Hence, to address this problem, we employ multiple antenna elements with a square-law combining energy detector in the W-CSS.

As business values pursued by today's organizations are abstract concepts, measurement of these values and their achievement is not straightforward. This paper proposes a value achievement measuring and managing framework, which recursively decomposes business values to construct a value hierarchy and then links it with the business process hierarchy. The framework makes it possible to measure value achievement, trace values to processes, and take necessary actions in response to the measured progress in value achievement.

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.

This paper customizes Goal/Question/Metric (GQM) project monitoring models for various projects and organizations to take advantage of the data from the software tool EPM and to allow the tailoring of the interpretation models based upon the context and success criteria for each project and organization. The basic idea is to build less concrete models that do not include explicit baseline values to interpret metrics values. Instead, we add hypothesis and interpretation layers to the models to help people of different projects make decisions in their own context. We applied the models to two industrial projects, and found that our less concrete models could successfully identify typical problems in software projects.

Accurate estimation of Software Code Size is important for developing cost-efficient embedded systems. The Code Size affects the amount of system resources needed, like ROM and RAM memory, and processing capacity. In our previous work, we have estimated the Code Size based on CFP (COSMIC Function Points) within 15% accuracy, with the purpose of deciding how much ROM memory to fit into products with high cost pressure. Our manual CFP measurement process would require 2.5 man years to estimate the ROM size required in a typical car. In this paper, we want to investigate how the manual effort involved in estimation of Code Size can be minimized. We define a UML Profile capturing all information needed for estimation of Code Size, and develop a tool for automated estimation of Code Size based on CFP. A case study will show how UML models save manual effort in a realistic case.

Random beamforming(RBF) is a simple and practical method that can realize multi-user multi-input multi-output (MU-MIMO) systems. In this letter, we analyze the average sum rate of RBF with minimum mean squared error (MMSE) receive beamforming. To this end, we exploit the empirical eigenvalue distribution [5] and extreme value theory. The numerical verification shows that the proposed analysis provides a good approximation of the average sum rate of RBF even for the small number of antennas.

In this paper, a contactless measurement technique of passive intermodulation (PIM) using a coaxial tube excited with standing waves is proposed. The principle of the proposed method is described using a two-port network model with the lumped resistances representing the losses of a specimen and test equipment. To show its validity, a test using nickel wires producing high PIM is carried out, and its PIM-dependency on DUT-position in the coaxial tube is simulated using the FDTD method. The simulated result shows a good agreement to the experiment. Through the examination, it is found that the power consumption by the PIM source in a specimen is essential in PIM production, and sensitive PIM detection does not require good matching condition. Finally, the relation between PIM-source size and generated PIM level is also examined. The result shows that at least 18 dB-PIM reduction is obtained by PIM source size in a half-wavelength conductive wire.

In this paper, the correspondence between the weighted line graph and the Mason signal flow graph (MSFG) has been established, which gives an interpretation of a convolutional network code (CNC) over a cyclic network from a different perspective. Furthermore, by virtue of Mason theorem, we present two new equivalent conditions to evaluate whether the global encoding kernels (GEKs) can be uniquely determined by the given complete set of local encoding kernels (LEKs) in a CNC over a cyclic network. These two new equivalent conditions turn out to be more intuitive. Moreover, we give an alternative simple proof of an existing result.

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, a new swept-frequency method for the measurement of the complex permittivity and permeability of materials is proposed. The method is based on the S-parameters measurement of a cylindrical material placed inside a rectangular waveguide, where the axis of the cylinder is perpendicular to the narrow waveguide walls. The usage of cylinders in measurement is beneficial because they are easy to fabricate and handle. A novel exact solution of the field scattered by the cylinder is developed. The solution is based on expanding the field in a sum of orthogonal modes in cylindrical coordinates. Excitation coefficients relating the cylindrical scattered field to the waveguide modes are derived, and are used to rigorously formulates the S-parameters. Measurement are performed in the S-band with two dielectric materials (PTFE, nylon), and in the X-band with one magnetic material (ferrite epoxy). The measurement results agree with those from the literature.

This paper presents a novel architecture design to optimize the reconfiguration process of a coarse-grained reconfigurable architecture (CGRA) called Reconfigurable Multimedia System II ( REMUS-II ). In REMUS-II, the tasks in multi-media applications are divided into two parts: computing-intensive tasks and control-intensive tasks. Two Reconfigurable Processor Units (RPUs) for accelerating computing-intensive tasks and a Micro-Processor Unit (µPU) for accelerating control-intensive tasks are contained in REMUS-II. As a large-scale CGRA, REMUS-II can provide satisfying solutions in terms of both efficiency and flexibility. This feature makes REMUS-II well-suited for video processing, where higher flexibility requirements are posed and a lot of computation tasks are involved. To meet the high requirement of the dynamic reconfiguration performance for multimedia applications, the reconfiguration architecture of REMUS-II should be well designed. To optimize the reconfiguration architecture of REMUS-II, a hierarchical configuration storage structure and a 3-stage reconfiguration processing structure are proposed. Furthermore, several optimization methods for configuration reusing are also introduced, to further improve the performance of reconfiguration process. The optimization methods include two aspects: the multi-target reconfiguration method and the configuration caching strategies. Experimental results showed that, with the reconfiguration architecture proposed, the performance of reconfiguration process will be improved by 4 times. Based on RTL simulation, REMUS-II can support the 1080p@32 fps of H.264 HiP@Level4 and 1080p@40 fps High-level MPEG-2 stream decoding at the clock frequency of 200 MHz. The proposed REMUS-II system has been implemented on a TSMC 65 nm process. The die size is 23.7 mm2 and the estimated on-chip dynamic power is 620 mW.

In the work we introduce novel approach to remote sensing from space for the estimation of sea wave heights with a spaceborne high precision two-frequency radar altimeter with nadir synthesis antenna aperture. Experiments show considerable reduction of the decorrelation factor of the correlation coefficient and so significant enhancement of the sensitivity of the altimeter for the estimation for the sea wave status.

In this letter, we address the issue of estimating the temporal dependence characteristic of link loss by using network tomography. We use a k-th order Markov chain (k > 1) to model the packet loss process, and estimate the state transition probabilities of the link loss model using a constrained optimization-based method. Analytical and simulation results indicate that our method yields more accurate packet loss probability estimates than existing loss inference methods.

As ROADMs (Reconfigurable Optical Add/Drop Multiplexers) are becoming widely used in metro/core networks, distributed control of wavelength paths by extended GMPLS (Generalized MultiProtocol Label Switching) protocols has attracted much attention. For the automatic establishment of an arbitrary wavelength path satisfying dynamic traffic demands over a ROADM or WXC (Wavelength Cross Connect)-based network, precise determination of chromatic dispersion over the path and optimized assignment of dispersion compensation capabilities at related nodes are essential. This paper reports an experiment over in-field fibers where GMPLS-based control was applied for the automatic discovery of chromatic dispersion, path computation, and wavelength path establishment with dynamic adjustment of variable dispersion compensation. The GMPLS-based control scheme, which the authors called GMPLS-Plus, extended GMPLS's distributed control architecture with attributes for automatic discovery, advertisement, and signaling of chromatic dispersion. In this experiment, wavelength paths with distances of 24 km and 360 km were successfully established and error-free data transmission was verified. The experiment also confirmed path restoration with dynamic compensation adjustment upon fiber failure.

The lateral velocity is of importance in cases like target identification and traffic management. Conventional Doppler methods are not capable of measuring lateral velocities since they quantify only the radial component. Based on the spectrogram characteristic of laterally moving targets, an algorithm based on fractional Fourier transform has been studied in the signal processing literature. The algorithm searches the peak position of the transformation, and calculates the lateral velocity from the peak position. The performance analysis of this algorithm is carried out in this paper, which shows that this algorithm approaches Cramer-Rao bound with reasonable computational complexity. Simulations are conducted at last to compare the analytical performance and the experimental result.