Tracking capsule endoscope location is one of the promising applications offered by implant body area networks (BANs). When tracking the capsule endoscope location, i.e., continuously localize it, it is effective to take the weighted sum of its past locations to its present location, in other words, to low-pass filter its past locations. Furthermore, creating an exact mathematical model of location transition will improve tracking performance. Therefore, in this paper, we investigate two tracking methods with received signal strength indicator (RSSI)-based localization in order to solve the capsule endoscope location tracking problem. One of the two tracking methods is finite impulse response (FIR) filter-based tracking, which tracks the capsule endoscope location by averaging its past locations. The other one is particle filter-based tracking in order to deal with a nonlinear transition model on the capsule endoscope. However, the particle filter requires that the particle weight is calculated according to its condition (namely, its likelihood value), while the transition model on capsule endoscope location has some model parameters which cannot be estimated from the received wireless signal. Therefore, for the purpose of applying the particle filter to capsule endoscope tracking, this paper makes some modifications in the resampling step of the particle filter algorithm. Our computer simulation results demonstrate that the two tracking methods can improve the performance as compared with the conventional maximum likelihood (ML) localization. Furthermore, we confirm that the particle filter-based tracking outperforms the conventional FIR filter-based tracking by taking the realistic capsule endoscope transition model into consideration.

In the arsenal of resources for improving computer memory system performance, predictors have gained an increasing role in the past few years. They can suppress the latencies when accessing cache or main memory. In our previous work we proposed predictors that not only close the opened DRAM row but also predict the next row to be opened, hence the name ‘Complete Predictor’. It requires less than 10kB of SRAM for a 2GB SDRAM system. In this paper we evaluate how much additional hardware is needed and whether the activations of the predictors will slow down the DRAM controller.

In order to analyze an impact of threshold voltage (Vth) fluctuation induced by random telegraph noise (RTN) on LSI circuit design, we measured a 40-nm 6-Tr-SRAM TEG which enables to evaluate individual bit-line current. RTN phenomenon was successfully measured and we also identified that the transfer MOSFET in an SRAM bit-cell was the most sensitive MOSFET. The proposed word line boosting technique, which applies slightly extra stress to the transfer MOSFET, improves about 30% of detecting probability of fail-bit cells caused by RTN.

We describe the recent progress on a Nb nine-layer fabrication process for large-scale single flux quantum (SFQ) circuits. A device fabricated in this process is composed of an active layer including Josephson junctions (JJ) at the top, passive transmission line (PTL) layers in the middle, and a DC power layer at the bottom. We describe the process conditions and the fabrication equipment. We use both diagnostic chips and shift register (SR) chips to improve the fabrication process. The diagnostic chip was designed to evaluate the characteristics of basic elements such as junctions, contacts, resisters, and wiring, in addition to their defect evaluations. The SR chip was designed to evaluate defects depending on the size of the SFQ circuits. The results of a long-term evaluation of the diagnostic and SR chips showed that there was fairly good correlation between the defects of the diagnostic chips and yields of the SRs. We could obtain a yield of 100% for SRs including 70,000JJs. These results show that considerable progress has been made in reducing the number of defects and improving reliability.

In this paper, a new method is proposed for unsupervised speckle level estimation in synthetic aperture radar (SAR) images. It is assumed that fully developed speckle intensity has a Gamma distribution. Based on this assumption, estimation of the equivalent number of looks (ENL) is transformed into noise variance estimation in the logarithmic SAR image domain. In order to improve estimation accuracy, texture analysis is also applied to exclude areas where speckle is not fully developed (e.g., urban areas). Finally, the noise variance is estimated by a 2-dimensional autoregressive (AR) model. The effectiveness of the proposed method is verified with several SAR images from different SAR systems and simulated images.

This paper introduces a comparison of three automatic gait generation methods for quadruped robots: GA (Genetic Algorithm), GP (genetic programming) and CPG (Central Pattern Generator). It aims to provide a useful guideline for the selection of gait generation methods. GA-based approaches seek to optimize paw locus in Cartesian space. GP-based techniques generate joint trajectories using regression polynomials. The CPGs are neural circuits that generate oscillatory output from an input coming from the brain. Optimizations for the three proposed methods are executed and analyzed using a Webots simulation of the quadruped robot built by Bioloid. The experimental comparisons and analyses provided herein will be an informative guidance for research of gait generation method.

Conventional adaptive notch filter based on an infinite impulse response (IIR) filter is well known. However, this kind of adaptive notch filter has a problem of stability due to its adaptive IIR filter. In addition, tap coefficients of this notch filter converge to solutions with bias error. In order to solve these problems, an adaptive notch filter using Fourier sine series (ANFF) is proposed. The ANFF is stable because an adaptive IIR filter is not used as an all-pass filter. Further, the proposed adaptive notch filter is robust enough to overcome effects of a disturbance signal, due to a structure of the notch filter based on an exponential filter and line symmetry of auto correlation.

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.

This letter deals with a new cell clustering problem subject to signal-to-interference-plus-noise-ratio (SINR) constraints in uplink network MIMO systems, where multiple base stations (BSs) cooperate for joint processing as forming a cluster. We first prove that the SINRs of users in a certain cluster always increase monotonically as the cluster size increases when the receiver filter that maximizes the SINR is used. Using this result, we propose an efficient clustering algorithm to minimize the maximum number of cooperative BSs in a cluster. Simulation results show that the maximum number of cooperative BSs minimized by the proposed method is close to that minimized by the exhaustive search and the proposed scheme outperforms the conventional one in terms of the outage probability.

A D2D (Device-to-Device) communication system needs to cope with inter-cell interference and other types of interferences between cellular network and D2D links. As a result, macro user equipments, particularly those located near a cell edge, will suffer from serious link performance degradation. We propose a novel interference avoidance mechanism assisted by the SRN (Shared Relay Node) in this letter. The SRN not only performs data re-transmission as a typical type-II relay, but has several newly defined features to avoid interference between cellular network and D2D links. The superb performance by the proposed scheme is evaluated through extensive system level simulations.

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.

One of the procedures for increasing the number of multi-input and multi-output (MIMO) branches without increasing the computational cost for MIMO detection or multiplexing is to exploit parallel transmissions by using polarization multiplexing. In this paper the effectiveness of using polarization multiplexing is confirmed under the existence of polarization rotation, which is inevitably present in short-range multi-input and multi-output (SR-MIMO) channels with planar array antennas. It is confirmed that 8×8 SR-MIMO transmission system with polarization multiplexing has 60bit/s/Hz of channel capacity. This paper also shows a model for theoretical cross polarization discrimination (XPD) degradation, which is useful to calculate XPD degradations on diagonal paths.

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.

Outsourcing to a cloud storage brings forth new challenges for the efficient utilization of computing resources as well as simultaneously maintaining privacy and security for the outsourced data. Data deduplication refers to a technique that eliminates redundant data on the storage and the network, and is considered to be one of the most-promising technologies that offers efficient resource utilization in the cloud computing. In terms of data security, however, deduplication obstructs applying encryption on the outsourced data and even causes a side channel through which information can be leaked. Achieving both efficient resource utilization and data security still remains open. This paper addresses this challenging issue and proposes a novel solution that enables data deduplication while also providing the required data security and privacy. We achieve this goal by constructing and utilizing equality predicate encryption schemes which allow to know only equivalence relations between encrypted data. We also utilize a hybrid approach for data deduplication to prevent information leakage due to the side channel. The performance and security analyses indicate that the proposed scheme is efficient to securely manage the outsourced data in the cloud computing.

In this letter, advanced QRD-M detection using iterative scheme is proposed. This scheme has a higher diversity degree than conventional QRD-M detection. According to the simulation results, the performance of proposed QRD-M detection is 0.5dB to 5.5dB better than the performance of conventional QRD-M detection and average iteration time is approximately 1 in the value of M = 1, 2, 3. Therefore, the proposed QRD-M detection has better performance than conventional QRD-M detection, particularly in a high SNR environment and low modulation order.

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.

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.

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.

Much work in cooperative communication has been done from the perspective of the physical and network layers. However, the exact impact of signal error rate performance on cooperative routing discovery still remains unclear in multihop ad hoc networks. In this paper, we show the symbol error rate (SER) performance improvement obtained from cooperative commutation, and examine how to incorporate the factor of SER into the distributed routing discovery scheme called DGCR (Dynamic Geographic Cooperative Routing). For a single cooperative communication hop, we present two types of metric to specify the degree that one node is suitable for becoming the relay node. One metric is the potential of a node to relay with optimal SER performance. The other metric is the distance of a node to the straight line that passes through the last forwarding node and the destination. Based on location knowledge and contention scheme, we combine the two metrics into a composite metric to choose the relay node. The forwarding node is chosen dynamically according to the positions of the actual relay node and the destination. Simulation results show that our approach outperforms non-cooperative geographic routing significantly in terms of symbol error rate, and that DGCR's SER performance is better than traditional geographic cooperative routing with slight path length increase.

In this work, a measurement-based procedure aimed at deriving a behavioral model of Bulk Current Injection (BCI) probes clamped onto multi-wire cable bundles is proposed. The procedure utilizes the measurement data obtained by mounting the probe onto the calibration jig for model-parameters extraction, and 2D electromagnetic simulations to adapt such parameters to the specific characteristics of the cable bundle under analysis. Outcome of the analysis is a behavioral model which can be easily implemented into the SPICE environment. Without loss of generality, the proposed model is here used to predict the radio-frequency noise stressing the terminal units of a two-wire harness. Model accuracy in predicting the common and differential mode voltages induced by BCI at the line terminals is assessed by EM modeling and simulation of the involved injection setup by the commercial software CST Microwave Studio.