Aiming at the problem of the deterioration of the contact performance caused by the wear debris generated during the fretting wear of the electrical connector, low-frequency fretting wear experiments were carried out on the contacts of electrical connectors, the accumulation and distribution of the wear debris were detected by the electrical capacitance tomography technology; the influence of fretting cycles, vibration direction, vibration frequency and vibration amplitude on the accumulation and distribution of wear debris were analyzed; the correlation between characteristic value of wear debris and contact resistance value was studied, and a performance degradation model based on the accumulation and distribution of wear debris was built. The results show that fretting wear and performance degradation are the most serious in axial vibration; the characteristic value of wear debris and contact resistance are positively correlated with the fretting cycles, vibration frequency and vibration amplitude; there is a strong correlation between the sum of characteristic value of wear debris and the contact resistance value; the prediction error of ABC-SVR model of fretting wear performance degradation of electrical connectors constructed by the characteristic value of wear debris is less than 6%. Therefore, the characteristic value of wear debris in contact subareas can quantitatively describe the degree of fretting wear and the process of performance degradation.

This paper proposes a network tomography scheme for information-centric networking (ICN), which we call ICN tomography. When content is received over a conventional IP network, the communication occurs after converting the content name into an IP address, which is the locator, so as to identify the position of the network. By contrast, in ICN, communication is achieved by directly specifying the content name or content ID. The content is sent to the requesting user by a nearby node having the content or cache, making it difficult to apply a conventional network tomography that uses end-to-end quality of service (QoS) measurements and routing information between the source and destination node pairs as input to the ICN. This is because, in ICN, the end-to-end flow for an end host receiving some content can take various routes; therefore, the intermediate and source nodes can vary. In this paper, we first describe the technical challenges of applying network tomography to ICN. We then propose ICN tomography, where we use the content name as an endpoint to define an end-to-end QoS measurement and a routing matrix. In defining the routing matrix, we assume that the end-to-end flow follows a probabilistic routing. Finally, the effectiveness of the proposed method is evaluated through a numerical analysis and simulation.

Active network monitoring based on Boolean network tomography is a promising technique to localize link failures instantly in transport networks. However, the required set of monitoring trails must be recomputed after each link failure has occurred to handle succeeding link failures. Existing heuristic methods cannot compute the required monitoring trails in a sufficiently short time when multiple-link failures must be localized in the whole of large-scale managed networks. This paper proposes an approach for computing the required monitoring trails within an allowable expected period specified beforehand. A random walk-based analysis estimates the number of monitoring trails to be computed in the proposed approach. The estimated number of monitoring trails are computed by a lightweight method that only guarantees partial localization within restricted areas. The lightweight method is repeatedly executed until a successful set of monitoring trails achieving unambiguous localization in the entire managed networks can be obtained. This paper demonstrates that the proposed approach can compute a small number of monitoring trails for localizing all independent dual-link failures in managed networks made up of thousands of links within a given expected short period.

The increased performance of mobile terminals has made it feasible to collect data using users' terminals. By making the best use of the network performance data widely collected in this way, network operators should deeply understand the current network conditions, identify the performance-degraded components in the network, and estimate the degree of their performance degradation. For their demands, one powerful solution with such end-to-end data measured by users' terminals is network tomography. Meanwhile, with the advance of network virtualization by software-defined networking, routing is dynamically changed due to congestion or other factors, and each end-to-end measurement flow collected from users may pass through different paths between even the same origin-destination node pair. Therefore, it is difficult and costly to identify through which path each measurement flow has passed, so it is also difficult to naively apply conventional network tomography to such networks where the measurement paths cannot be uniquely determined. We propose a novel network tomography for the networks with undeterministic routing where the measurement flows pass through multiple paths in spite of the origin-destination node pair being the same. The basic idea of our method is to introduce routing probability in accordance with the aggregated information of measurement flows. We present two algorithms and evaluate their performances by comparing them with algorithms of conventional tomography using determined routing information. Moreover, we verify that the proposed algorithms are applicable to a more practical network.

An electrical capacitance tomography (ECT) method was used to detect fretting wear behavior of electrical connectors. The specimens used in this study were contacts of type-M round two-pin electrical connectors. The experiments consisted of running a series of vibration tests at each frequency combined with one g levels. During each test run, the measured capacitance per pair of electrodes was monitored as a performance characteristic, which is induced by the wear debris generated by the fretting wear of electrical connectors. The fretted surface is examined using scanning electron microscopy (SEM) and energy dispersive spectrometer (EDS) analysis to assess the surface profile, extent of fretting damage and elemental distribution across the contact zone and then compared to the capacitance values. The results exhibit that with the increase of the fretting cycles or the vibration frequency, the characteristic value of the wear debris between the contacts of electrical connector gradually increases and the wear is more serious. Measured capacitance values are consistent with SEM and EDS analysis.

In this paper, we consider network monitoring techniques to estimate communication qualities in wide-area mobile networks, where an enormous number of heterogeneous components such as base stations, routers, and servers are deployed. We assume that average delays of neighboring base stations are comparable, most of servers have small delays, and delays at core routers are negligible. Under these assumptions, we propose Heterogeneous Delay Tomography (HDT) to estimate the average delay at each network component from end-to-end round trip times (RTTs) between mobile terminals and servers. HDT employs a crowdsourcing approach to collecting RTTs, where voluntary mobile users report their empirical RTTs to a data collection center. From the collected RTTs, HDT estimates average delays at base stations in the Graph Fourier Transform (GFT) domain and average delays at servers, by means of Compressed Sensing (CS). In the crowdsourcing approach, the performance of HDT may be degraded when the voluntary mobile users are unevenly distributed. To resolve this problem, we further extend HDT by considering the number of voluntary mobile users. With simulation experiments, we evaluate the performance of HDT.

SAR tomography is one of the methods that can perform 3-dimensional (3-D) imaging with multiple SAR datasets by using the Direction-of-arrival (DOA) estimation technique to estimate the height distribution of scatterers. Several reports on SAR tomography have been issued. However, experimental results of the SAR tomography by the Pi-SAR2-X, Japanese airborne SAR operated by the NICT, have not been reported yet. This paper is the first to report the results of experiments on the Japanese SAR platform. High-resolution 2-dimensional image can be obtained by the X-band SAR. However the image is generated by projecting 3-D objects in to a 2-D image plane, hence the target responses having the same slant-range distance locate at the same image pixel. This is well known as the layover problem. When we employ the X-band SAR tomography, we can obtain 3-D high-resolution images without the layover and also foreshortening problem. It will be useful for disaster damage monitoring, especially in urban areas. The main difficulty of the SAR tomography comes from the phase error caused by inaccurate flight-path data. In many cases, the dataset are preprocessed and compensated so as to parallelize their flight-path to carry out the phase calibration and the DOA estimation easily. However, it is often difficult for common users to obtain such preprocessed datasets. In this paper, we propose a simple calibration method by using a flat-surface area with known altitude. Experiments show that the proposed method is effective for the Pi-SAR2-X standard products without parallelized preprocessing or precise flight-path information.

Precise estimation of coronary arteries from computed tomography angiography (CTA) data is one of the challenging problems. This study focuses on automatic delineation of coronary arteries from 3D CTA data that may assess the clinicians in identifying the coronary pathologies. In this work, we present a technique that effectively segments the complete coronary arterial tree under the guidance of initial vesselness response without relying on heavily manual operations. The proposed method isolates the coronary arteries with accuracy by using localized statistical energy model in two directions provided with an automated seed which ensures an optimal segmentation of the coronaries. The detection of seed is carried out by analyzing the shape information of the coronary arteries in three successive cross-sections. To demonstrate the efficiency of the proposed algorithm, the obtained results are compared with the reference data provided by Rotterdam framework for lumen segmentation and the level-set active contour based method proposed by Lankton et al. Results reveal that the proposed method performs better in terms of leakages and accuracy in completeness of the coronary arterial tree.

We developed an electrically driven near-infrared broadband light source based on self-assembled InAs quantum dots (QDs). By combining emissions from four InAs QD ensembles with controlled emission center wavelengths, electro-luminescence (EL) with a Gaussian-like spectral shape and approximately 85-nm bandwidth was obtained. The peak wavelength of the EL was blue-shifted from approximately 1230 to 1200 nm with increased injection current density (J). This was due to the state-filling effect: sequential filling of the discrete QD electron/hole states by supplied carriers from lower (ground state; GS) to higher (excited state; ES) energy states. The EL intensities of the ES and GS emissions exhibited different J dependence, also because of the state-filling effect. The point-spread function (PSF) deduced from the Fourier-transformed EL spectrum exhibited a peak without apparent side lobes. The half width at half maximum of the PSF was 6.5 µm, which corresponds to the estimated axial resolution of the optical coherence tomography (OCT) image obtained with this light source. These results demonstrate the effectiveness of the QD-based device for realizing noise-reduced high-resolution OCT.

In recent years, with the popularization of video collection devices and the development of the Internet, it is easy to copy original digital videos and distribute illegal copies quickly through the Internet. It becomes a critical task to uphold copyright laws, and this problem will require a technical solution. Therefore, as a challenging problem, copy detection or video identification becomes increasingly important. The problem addressed here is to identify a given video clip in a given set of video sequences. In this paper, an extension to the video identification approach based on video tomography is presented. First, the feature extraction process is modified to enhance the reliability of the shot signature with its size unchanged. Then, a new similarity measurement between two shot signatures is proposed to address the problem generated by the original approach when facing the query shot with a short length. In addition, the query scope is extended from one shot only to one clip (several consecutive shots) by giving a new definition of similarity between two clips and describing a search algorithm which can save much of the computation cost. Experimental results show that the proposed approach is more suitable for identifying shots with short lengths than the original approach. The clip query approach performs well in the experiment and it also shows strong robustness to data loss.

The “Blind Men and an Elephant” is an old Indian story about a group of blind men who encounter an elephant and do not know what it is. This story describes the difficulties of understanding a large concept or global view based on only local information. Modern technologies enable us to easily obtain and retain local information. However, simply collecting local information does not give us a global view, as evident in this old story. This paper gives a concrete model of this story on the plane to theoretically and mathematically discuss it. It analyzes what information we can obtain from collected local information. For a convex target object modeling the elephant and a convex sensing area, it is proven that the size and perimeter length of the target object are the only parameters that can be observed by randomly deployed sensors modeling the blind men. To increase the number of observable parameters, this paper argues that non-convex sensing areas are important and introduces composite sensor nodes as an approach to implement non-convex sensing areas. The paper also derives a model on the discrete space and analyzes it. The analysis results on the discrete space are applicable to some network related issues such as link quality estimation in a part of a network based on end-to-end probing.

Network tomography is a technique for estimating internal network characteristics from end-to-end measurements. In this paper, we focus on loss tomography, which is a network tomography problem for estimating link loss rates. We study a loss tomography problem to detect links with high link loss rates in network environments with dynamically changing link loss rates, and propose a window-based sequential loss tomography scheme. The loss tomography problem is formulated as an underdetermined linear inverse problem, where there are infinitely many candidates of the solution. In the proposed scheme, we use compressed sensing, which can solve the problem with a prior information that the solution is a sparse vector. Measurement nodes transmit probe packets on measurement paths established between them, and calculate packet loss rates of measurement paths (path loss rates) from probe packets received within a window. Measurement paths are classified into normal quality and low quality states according to the path loss rates. When a measurement node finds measurement paths in the low quality states, link loss rates are estimated by compressed sensing. Using simulation scenarios with a few link states changing dynamically from low to high link loss rates, we evaluate the performance of the proposed scheme.

Three dimensional (3D) terahertz (THz) imaging or THz tomography has recently proven to be useful for non-destructive testing of industrial materials and structures. In place of previous imaging techniques such as THz pulse or continuous wave (CW) radar, we propose a THz optical coherence tomography (OCT) using frequency-swept THz sources, and demonstrate 3D imaging. In addition, we further apply this technique to the millimeter-wave region in order to extend applicable targets.

We consider the problem of detecting and localizing of link quality degradations in transparent wavelength division multiplexing (WDM) networks. In particular, we consider the degradation of the optical signal-to-noise ratio (OSNR), which is a key parameter for link quality monitoring in WDM networks. With transparency in WDM networks, transmission lightpaths can bypass electronic processing at intermediate nodes. Accordingly, links cannot always be monitored by receivers at their end nodes. This paper proposes the use of optical multicast probes to monitor OSNR degradations on optical links. The proposed monitoring scheme consists of two steps. The first step is an off-line process to set up monitoring trees using integer linear programming (ILP). The set of monitoring trees is selected to guarantee that significant OSNR degradations can be identified on any link or links in the network. The second step uses optical performance monitors that are placed at the receivers identified in the first step. The information from these monitors is collected and input to the estimation algorithm to localize the degraded links. Numerical results indicate that the proposed monitoring algorithm is able to detect link degradations that cause significant OSNR changes. In addition, we demonstrate how the information obtained from monitoring can be used to detect a significant end-to-end OSNR degradation even though there is no significant OSNR degradation on individual links.

Network tomography is an inference technique for internal network characteristics such as link loss rate and link delay from end-to-end measurements. In this paper, we consider network tomography for link loss rates, which is referred to as loss tomography. We propose a loss tomography scheme with bitwise operation-based in-network processing. Intermediate nodes generate coded packets by performing bitwise-operations on received packets so as to embed information about paths along which those packets have been transmitted. The coded packets are then forwarded to downstream nodes. In this way, receiver nodes obtain information about paths along which packets are transmitted successfully. Moreover, we show a recursion to compute the likelihood function of path loss rates, which can be utilized in estimating link loss rates from path loss information.

We use end-to-end measurements to address the problem of fault diagnosis in computer networks. Since link-level characteristics cannot be uniquely determined from available end-to-end measurements, most existing diagnosis approaches make statistical assumptions of the network to obtain a unique solution. However, the performance of these approaches is not assured due to the uncertainty of the assumptions. Thus the diagnostic accuracy cannot be guaranteed. In this paper, we propose a different paradigm for fault diagnosis which can find all identifiable links and the minimal identifiable link sequences, and infer their loss rates with the least error. Compared with a former representative diagnosis method through experiments, the experimental results show that our method has smaller diagnosis granularity and much less running time for most network topologies. We also conducted experiments using 105 Planetlab hosts. The results validate the performance of our method as well.

Network tomography is an appealing technology to infer link delay distributions since it only relies on end-to-end measurements. However, most approaches in network delay tomography are usually computationally intractable. In this letter, we propose a Fast link Delay distribution Inference algorithm (FDI). It estimates the node cumulative delay distributions by explicit computations based on a subtree-partitioning technique, and then derives the individual link delay distributions from the estimated cumulative delay distributions. Furthermore, a novel discrete delay model where each link has a different bin size is proposed to efficiently capture the essential characteristics of the link delay. Combining with the variable bin size model, FDI can identify the characteristics of the network-internal link delay quickly and accurately. Simulation results validate the effectiveness of our method.

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.

A Fourier domain optical coherence tomography system for obtaining a two-dimensional image is constructed. Imaging characteristics of the OCT system in a transverse direction are experimentally investigated. Angle dependence of reflection intensity from a smooth surface is clearly observed and analyzed with consideration of spatial mode coupling to a fiber.

We developed advanced techniques for the growth of self-assembled quantum dots (QDs) for fabricating a broadband light source that can be applied to optical coherence tomography (OCT). Four QD ensembles and strain reducing layers (SRLs) were grown in selective areas on a wafer by the use of a 90° rotational metal mask. The SRL thickness was varied to achieve appropriate shifts in the peak wavelength of the QD emission spectrum of up to 120 nm. The four-color QD ensembles were expected to have a broad bandwidth of more than 160 nm due to the combination of excited state emissions when introduced in a current-induced broadband light source such as a superluminescent diode (SLD). Furthermore, a desired shape of the SLD spectrum can be obtained by controlling the injection current applied to each QD ensemble. The broadband and spectrum shape controlled light source is promising for high-resolution and low-noise OCT systems.