This paper derives the balanced realizations of second-order analog filters directly from the transfer function. Second-order analog filters are categorized into the following three cases: complex conjugate poles, distinct real poles, and multiple real poles. For each case, simple formulas are derived for the synthesis of the balanced realizations of second-order analog filters. As a result, we obtain closed form expressions of the balanced realizations of second-order analog filters.

In a cognitive radio (CR) network, the channel sensing scheme used to detect the existence of a primary user (PU) directly affects the performances of both CR and PU. However, in practical systems, the CR is prone to sensing errors due to the inefficiency of the sensing scheme. This may yield primary user interference and low system performance. In this paper, we present a learning-based scheme for channel sensing in CR networks. Specifically, we formulate the channel sensing problem as a partially observable Markov decision process (POMDP), where the most likely channel state is derived by a learning process called Fuzzy Q-Learning (FQL). The optimal policy is derived by solving the problem. Simulation results show the effectiveness and efficiency of our proposed scheme.

This paper describes an analytical study of performance of a proposed signal detection scheme that will allow coexistence of an additional radio communication system (generally, secondary system) in the service area where the existing communication system (primary system) is operated. Its performance characteristics are derived by an analytical method based on stochastic theory, which is subsequently validated by software simulation. The main purpose of the detection scheme is to protect the primary system from the secondary system. In such a situation, the signals of the primary system and secondary system may be simultaneously received in the signal detector. One application of such a scheme is D-to-D (Device-to-Device) communication, whose system concept including the detection scheme is briefly introduced. For improved secondary signal detection, we propose the signal cancellation method of the primary system and the feature detection method of the secondary system signal. We evaluate the performance characteristics of the detection scheme in terms of “probability of correct detection”. We reveal that an undesired random component is produced in the feature detection procedure when two different signals are simultaneously received, which degrades the detection performance. Such undesired component is included in the analytical equations. We also clarify that the cancellation scheme improves the performance, when the power ratio of the primary signal to secondary signal is higher than 20-22dB.

Spectrum sensing is one of the methods to identify available white spaces for secondary usage which was specified by the regulators. However, signal quality to be sensed can plunge to a very low signal-to-noise-ratio due to signal propagation and hence readings from individual sensors will be unreliable. Distributed sensing by the cooperation of multiple sensors is one way to cope with this problem because the diversity gain due to the combining effect of data captured at different position will assist in detecting signals that might otherwise not be detected by a single sensor. In effect, the probability of detection can be improved. We have implemented a distributed sensing system to evaluate the performance of different cooperative sensing algorithms. In this paper we describe our implementation and measurement experience which include the system design, specification of the system, measurement method, the issues and solutions. This paper also confirms the performance enhancement offered by distributed sensing algorithms, and describes several ideas for further enhancement of the sensing quality.

Television white spaces (TVWS) are locally and/or temporally unused portions of TV bands. After TVWS regulations were passed in the USA, more and more regulators have been considering efficient use of TVWS. Under the condition that the primary user, i.e., terrestrial TV broadcasting system, is not interfered, various secondary users (SUs) may be deployed in TVWS. In Japan, the TVWS regulations started with broadcast-type SUs and small-area broadcasting systems, followed by voice radio. This paper aims to provide useful insights for more efficient utilization of TVWS as one of the options to meet the continuously increasing demand for wireless bandwidth. TVWS availability in Japan is analyzed using graphs and maps. As per the regulations in Japan, for TV broadcasting service, a protection contour is defined to be 51dBµV/m, while the interference contour for SU is defined to be 12.3dBµV/m. We estimate TVWS availability using these two regulation parameters and the minimum separation distances calculated on the basis of the ITU-R P.1546 propagation models. Moreover, we investigate and explain the effect of two important factors on TVWS availability. One is the measures to avoid adjacent channel interference, while the other is whether the SU has client devices with interference ranges beyond the interference area of the master device. Furthermore, possible options to increase available TVWS channels are discussed.

A covariance-based algorithm is proposed to find a barrage jammer suppression filter for surveillance radar with an adaptive array. The conventional adaptive beamformer (ABF) or adaptive sidelobe canceller (ASLC) with auxiliary antennas can be used successfully in sidelobe jammer rejection. When a jammer shares the same bearing with the target of interest, however, those methods inherently cancel the target in their attempt to null the jammer. By exploiting the jammer multipath scattered returns incident from other angles, the proposed algorithm uses only the auto-covariance matrix of the sample data produced by stacking range cell returns in a pulse repetition interval (PRI). It does not require estimation of direction of arrival (DOA) or time difference of arrival (TDOA) of multipath propagation, thus making it applicable to electronic countermeasure (ECM) environments with high power barrage jammers and it provides the victim radar with the ability to null both the sidelobe (sidebeam) and mainlobe (mainbeam) jammers simultaneously. Numeric simulations are provided to evaluate the performance of this filter in the presence of an intensive barrage jammer with jammer-to-signal ratio (JSR) greater than 30dB, and the achieved signal-to-jammer-plus-noise ratio (SJNR) improvement factor (IF) exceeds 46dB.

The percentage of pedestrian deaths in traffic accidents is on the rise in Japan. In recent years, there have been calls for measures to be introduced to protect vulnerable road users such as pedestrians and cyclists. In this study, a method to detect and track pedestrians using an in-vehicle camera is presented. We improve the technology of detecting pedestrians by using the highly accurate images obtained with a monocular camera. In the detection step, we employ ECoHOG as the feature descriptor; it accumulates the integrated gradient intensities. In the tracking step, we apply an effective motion model using optical flow and the proposed feature descriptor ECoHOG in a tracking-by-detection framework. These techniques were verified using images captured on real roads.

Lane detection plays an important role in Driver Assistance Systems and Autonomous Vehicle System. In this paper, we propose a parallel-snake model combined with balloon force for lane detection. Parallel-snake is defined as two open active contours with parallel constrain. The lane boundaries on the left and right sides are assumed as parallel curves, parallel-snake is deformed to estimate these two boundaries. As lane regions between left and right boundaries usually have low gradient, snake will lose external force on these regions. Furthermore, inspired by balloon active contour model, the balloon force is introduced into parallel-snake to expand two parallel curves from center of road to the left and right lane boundaries. Different from closed active contour, stretching force is adopted to prevent the head and tail of snake from converging together. The experimental results on three different datasets show that parallel-snake model can work well on images with shadows and handle the lane with broken boundaries as the parallel property.

This paper reports the use of haptic augmented reality in breast tumor palpation. In general, lumps in the breast are stiffer than surrounding tissues, allowing us to haptically detect them through self-palpation. The goal of the study is to assist self-palpation of lumps by haptically augmenting stiffness around lumps. The key steps are to estimate non-linear stiffness of normal tissues in the offline preprocessing step, detect areas that show abnormally stiffer responses, and amplify the difference in stiffness through a haptic augmented reality interface. The performance of the system was evaluated in a user-study, demonstrating the potential of the system.

This paper summarizes the current status of regulations, standardization efforts and trials around the world regarding white space (WS) communications, especially television band WS (TVWS). After defining WS communication systems configurations and function and the categories of white space database, the TVWS regulations in United States, United Kingdom, and Japan are summarized. Then regarding status of standardization for TVWS devices, IEEE 802 and IEEE 1900 standards are summarized. Finally ongoing pilot projects and trials of WS communications in the world are summarized, and trends and future direction of research on WS communication systems are summarized.

This letter deals with a sparse signal recovery problem and proposes a new algorithm based on the iterative reweighted least squares (IRLS) algorithm. We assume that the non-zero values of a sparse signal is always greater than a given constant and modify the IRLS algorithm to satisfy this assumption. Numerical results show that the proposed algorithm recovers a sparse vector efficiently.

As a promising lamination-loss-free fabrication technique, diffusion bonding of etched thin metal plates is used to realize double-layer waveguide slot antennas. Alternating-phase feed is adopted in this paper to reduce the number of laminated plates to simplify fabrication as well as to reduce cost. A 20 × 20-element double-layer waveguide slot antenna with a bottom partially-corporate feed circuit is designed for 39GHz band operation as an example. The adjacent radiating waveguides as well as the 2 × 2 sub-arrays fed in an alternating-phase manner eliminate the need for complete electrical contact in the top layer. However, the feed circuit in the bottom layer has to be completely diffusion-bonded. These two layers are simply assembled by screws. An antenna laminated by only diffusion bonding is also fabricated and evaluated for comparison. The comparison proved that the simply fabricated antenna is comparable in performance to the fully diffusion-bonded one.

Formalizing requirements in formal specifications is an effective way to deepen the understanding of the envisioned system and reduce ambiguities in the original requirements. However, it requires mathematical sophistication and considerable experience in using formal notations, which remains a challenge to many practitioners. To handle this challenge, this paper describes a pattern-based approach to facilitate the formalization of requirements. In this approach, a pattern system is pre-defined to guide requirements formalization where each pattern provides a specific solution for formalizing one kind of function into a formal expression. All of the patterns are classified and organized into a hierarchical structure according to the functions they can be used to formalize. The distinct characteristic of our approach is that all of the patterns are stored on computer as knowledge for creating effective guidance to facilitate the developer in requirements formalization; they are “understood” only by the computer but transparent to the developer. We also describe a prototype tool that supports the approach. It adopts Hierarchical Finite State Machine (HFSM) to represent the pattern knowledge and implements an algorithm for applying it to assist requirements formalization. Two experiments on the tool are presented to demonstrate the effectiveness of the approach.

Web page segmentation has a variety of benefits and potential web applications. Early techniques of web page segmentation are mainly based on machine learning algorithms and rule-based heuristics, which cannot be used for large-scale page segmentation. In this paper, we propose a formulated page segmentation method using visual semantics. Instead of analyzing the visual cues of web pages, this method utilizes three measures to formulate the visual semantics: layout tree is used to recognize the visual similar blocks; seam degree is used to describe how neatly the blocks are arranged; content similarity is used to describe the content coherent degree between blocks. A comparison experiment was done using the VIPS algorithm as a baseline. Experiment results show that the proposed method can divide a Web page into appropriate semantic segments.

This paper describes a novel method for the bi-directional transformation between the power consumption patterns of appliances and human living activities. We have been proposing a demand-side energy management system that aims to cut down the peak power consumption and save the electric energy in a household while keeping user's quality of life based on the plan of electricity use and the dynamic priorities of the appliances. The plan of electricity use could be established in advance by predicting appliance power consumption. Regarding the priority of each appliance, it changes according to user's daily living activities, such as cooking, bathing, or entertainment. To evaluate real-time appliance priorities, real-time living activity estimation is needed. In this paper, we address the problem of the bi-directional transformation between personal living activities and power consumption patterns of appliances. We assume that personal living activities and appliance power consumption patterns are related via the following two elements: personal appliance usage patterns, and the location of people. We first propose a Living Activity - Power Consumption Model as a generative model to represent the relationship between living activities and appliance power consumption patterns, via the two elements. We then propose a method for the bidirectional transformation between living activities and appliance power consumption patterns on the model, including the estimation of personal living activities from measured appliance power consumption patterns, and the generation of appliance power consumption patterns from given living activities. Experiments conducted on real daily life demonstrate that our method can estimate living activities that are almost consistent with the real ones. We also confirm through case study that our method is applicable for simulating appliance power consumption patterns. Our contributions in this paper would be effective in saving electric energy, and may be applied to remotely monitor the daily living of older people.

This letter proposes an efficient compression scheme for the copyright- and privacy-protected image trading system. The proposed scheme multiplies pseudo random signs to amplitude components of discrete cosine transformed coefficients before the inverse transformation is applied. The proposed scheme efficiently compresses amplitude-only image which is the inversely transformed amplitude components, and the scheme simultaneously improves the compression efficiency of phase-only image which is the inversely transformed phase components, in comparison with the conventional systems.

As one of organic electroluminescent (EL) materials, we developed a method of fabricating an ink using low molecular- weight materials with a long emission lifetime for application to the inkjet method. Although the emission lifetime is usually long for low molecular-weight materials, their high manufacturing cost due to the necessity of vapor deposition is a disadvantage. We utilized the low molecular-weight material, tris-(8-hydroxyquinoline) aluminum (Alq3), and investigated its dispersibility in a solvent in which it has low solubility. In addition, we ascertained whether the material could maintain its photoluminescence characteristic under the irradiation of ultraviolet rays by investigating the emission of photoluminescence. Alq3 was crystallized into nanosize crystals, whose surface was then coated with a primary amine by the gas evaporation method. The fabricated ink contained crystals with an average size of 250nm and high dispersibility in tetradecane, in which Alq3 is insoluble. Thus, we made it possible to carry out an inkjet method with low molecular weight EL materials.

In this paper, the measurement of capacitance variation, of an on-chip power distribution network (PDN) due to the change of internal states of a CMOS logic circuit, is studied. A state-dependent PDN-capacitance model that explains measurement results will be also proposed. The model is composed of capacitance elements related to MOS transistors, signal and power supply wires, and substrate. Reflecting the changes of electrode potentials, the capacitance elements become state-dependent. The capacitive elements are then all connected in parallel between power supply and ground to form the proposed model. By using the proposed model, state-dependence of PDN-capacitances for different logic circuits are studied in detail. The change of PDN-capacitance exceeds 12% of its total capacitance in some cases, which corresponds to 6% shift of anti-resonance frequency. Consideration of the state-dependence is important for modeling the PDN-capacitance.

In collaborative software developments, many change processes implementing change requests are executed concurrently by different workers. The fact that the workers do not have sufficient information about the others' work and complicated dependencies among artifacts can lead to unexpected inconsistencies among the artifacts impacted by the changes. Most previous studies concentrated only on concurrent changes and considered them separately. However, even when the changes are not concurrent, inconsistencies may still happen if a worker does not recognize the impact of the changes made by other workers on his changes or the impact of his changes on other workers' changes. In addition, the changes in a change process are related to each other through their common target of realizing the change request and the dependencies among the changed artifacts. Therefore, to handle inconsistencies more effectively, we concentrate on both concurrent and non-concurrent changes, and the context of a change, i.e. the change process containing the change, rather than the ongoing changes only. In this paper, we present an inconsistency awareness mechanism and a Change Support Workflow Management System (CSWMS) that realizes this mechanism. By monitoring the progress of the change processes and the ongoing changes in the client workspaces, CSWMS can notify the workers of a (potential) inconsistency in advance along with the context of the inconsistency, that is, the changes causing the inconsistency and the change processes containing these changes. Based on the information provided by CSWMS, the workers can detect and resolve inconsistencies more easily and quickly. Therefore, our research can contribute to building a safer and more efficient collaborative software development environment.

Regularized forward selection is viewed as a method for obtaining a sparse representation in a nonparametric regression problem. In regularized forward selection, regression output is represented by a weighted sum of several significant basis functions that are selected from among a large number of candidates by using a greedy training procedure in terms of a regularized cost function and applying an appropriate model selection method. In this paper, we propose a model selection method in regularized forward selection. For the purpose, we focus on the reduction of a cost function, which is brought by appending a new basis function in a greedy training procedure. We first clarify a bias and variance decomposition of the cost reduction and then derive a probabilistic upper bound for the variance of the cost reduction under some conditions. The derived upper bound reflects an essential feature of the greedy training procedure; i.e., it selects a basis function which maximally reduces the cost function. We then propose a thresholding method for determining significant basis functions by applying the derived upper bound as a threshold level and effectively combining it with the leave-one-out cross validation method. Several numerical experiments show that generalization performance of the proposed method is comparable to that of the other methods while the number of basis functions selected by the proposed method is greatly smaller than by the other methods. We can therefore say that the proposed method is able to yield a sparse representation while keeping a relatively good generalization performance. Moreover, our method has an advantage that it is free from a selection of a regularization parameter.