An interactive lung field segmentation scheme with automated capability

Feasible clinical application of any automated segmenting methodology demands more than just accuracy. Amendment to the automated delineation is necessary when the algorithm fails, however, integrated solution to such a scenario is largely absent in literature. Hence in this survey we devised an architecture that does both the automated and interactive lung field localizations using a single segmenting engine—random walker algorithm—so that intuitive amendment is only necessary when the automated generated delineation is unsatisfactory. The algorithm proceeds by first extracting 18 intensity profiles running horizontally, each of them equally spacing apart, and in each intensity profile three extreme points denoting the two lungs and the esophagus are determined through profile matching. This done, the algorithm removes profiles that do not intersect with the lung, and the rest of the extreme points are plugged into random walker algorithm to perform segmentation. The achieved accuracy in localization by the above was 0.8875 in terms of overlap measure (the maximum value for this parameter is 1) over 341 images. In the case where unsatisfactory delineation prompts amendment necessary, the user can interactively segment the lung by just a shift on some of the previous-determined points to the desired locations, and random walker algorithm is run again with the amended input. By such a fusion, the benefits of both the automated and interactive segmentation are shared in a single architecture.     

Pitchfork bifurcation and flip-flop operation with a coupled nonlinear system

A ring cavity system consisting of two hybrid Michelson interferometers coupled together with feedback is constructed. This system shows spatial bifurcation and can be utilized as an all-optical flip-flop device. We demonstrate experimentally a flip-flop operation by use of only a positive pulse in this system.     

Metal Ions versus Protons: Tracking of Charge-Carrier Insertion into a Cathode Oxide in Aqueous Rechargeable Batteries

Protons in aqueous electrolytes can perform as an additional type of charge carrier for insertion/extraction in addition to the primary carrier cations in aqueous rechargeable batteries. Despite many diverse claims regarding the effect of protons, mutually conflicting experimental results and their interpretations without direct evidence have been reported over the last decade. Systematic examinations and analyses are thus imperative to clarify the conditions of proton insertion in aqueous rechargeable batteries. Utilizing V₂O₅ as a model cathode and beaker-type cells with a sufficient amount of ZnSO₄ aqueous electrolytes in this work, it is demonstrated that protons are inserted into the cathode prior to Zn-ions in low-pH conditions (pH ≤ 3.0). In stark contrast, the influence of protons on the discharge voltage and capacity is insignificant, when either the pH becomes higher (pH ≥ 4.0) or the electrolyte volume is considerably low in coin-type cells. Similar behavior of pH-dependent proton insertion is also verified in Na–, Mg–, and Al-ion electrolytes. Providing a resolution to the controversy regarding proton insertion, the present study emphasizes that the influence of protons substantially varies depending on the pH and relative volume of electrolytes in aqueous batteries.     

On measuring network robustness for weighted networks

Knowledge and Information Systems - Network robustness measures how well network structure is strong and healthy when it is under attack, such as vertices joining and leaving. It has been widely...     

Metal microparticle – Polymer composites as printable,bio/ecoresorbable conductive inks

Biologically and environmentally resorbable electronic devices support application possibilities that cannot be addressed with conventional technologies. This paper presents highly conductive, water-soluble composites that can be printed to form contacts, interconnects, antennas, and other important features that are essential to nearly all systems of this type. An optimized material formulation involves in situ polymerization to yield a polyanhydride containing a dispersion of molybdenum microparticles at appropriate concentrations. Comparisons of essential physical and electrical properties of these materials to those of composites formed with other polymers and other metal microparticles reveal the relevant considerations. Various functional demonstrations of screen-printed test structures and devices illustrate the suitability of these conductive inks for use in water-soluble electronic devices. A key advantage of the material introduced here compared to alternatives is its ability to maintain conductance over significant periods of time while immersed in relevant aqueous solutions. Studies involving live animal models establish the biocompatibility.     

Absorption effect in the calculation of a second-order nonlinear coefficient from the data of a maker fringe experiment

The effect of light absorption by sample in the analysis of Makerfringe data for estimating a second-order nonlinear coefficient hasbeen studied experimentally. Two theories, one by Jerphagnon andKurtz that neglects the absorption effect and one by Herman and Haydenthat takes into account the absorption effect, were compared with theexperimental results. It was found that Jerphagnon and Kurtz'sformula was unable to predict correctly not only the magnitude but alsothe incident angle dependence or the sample thickness dependence of thesecond harmonic signal generated by the sample with strong absorption, whereas the theory by Herman and Hayden was able to make thosepredictions fairly well. It was also found that the error in theestimated nonlinear coefficient when one uses Jerphagnon and Kurtz'sformula could be as large as 2-4 times the true value, depending onsample thickness.     

A study of a new data association and track initiation method with normalized distance squared ordering

In an underwater environment, measurements regarding true targets and false targets (clutter) can be made. Therefore, a suitable data association method to exactly detect and track a target and an efficient track initiation method for judging tracks formed by the target should be selected in this environment. This paper attempts to propose a new data association method and track initiation method to detect and track targets more effectively. Also, the performance of the new method is tested in a series of Monte Carlo simulation runs and is compared with the existing data association and track initiation methods in a cluttered environment.     

A comparative study of two techniques for improving power‐handling capability of CMOS T/R switches

This article proposes an asymmetric topology for transmit/receive (T/R) switches and more importantly presents a comparative study of both LC‐tuned and resistive body‐floating techniques for improving the power‐handling capability of the T/R switches in the same 0.18‐μm triple‐well CMOS. It is shown from simulations and measurements that the switches adopting either technique achieve comparable performances. For instance, the switch employing the LC‐tuned body‐floating technique exhibits insertion loss of 1.5 dB, isolation of 23.5 dB, and power‐handling capability of 22.5 dBm at 5.2 GHz, whereas the switch using the resistive body‐floating technique exhibits insertion loss of 1.3 dB, isolation of 24 dB, and power‐handling capability of 22.2 dBm, respectively. Therefore, one can conclude that the asymmetric topology with the resistive body‐floating technique is more suitable for designing T/R switches for wireless local area network applications as it consumes smaller silicon area. © 2010 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2010.     

An Artificial Neural Network Classifier Design Based-on Variable Kernel and Non-Parametric Density Estimation

This paper proposes a probabilistic variant of the SOM-kMER (Self Organising Map-kernel-based Maximum Entropy learning Rule) model for data classification. The classifier, known as pSOM-kMER (probabilistic SOM-kMER), is able to operate in a probabilistic environment and to implement the principles of statistical decision theory in undertaking classification problems. A distinctive feature of pSOM-kMER is its ability in revealing the underlying structure of data. In addition, the Receptive Field (RF) regions generated can be used for variable kernel and non-parametric density estimation. Empirical evaluation using benchmark datasets shows that pSOM-kMER is able to achieve good performance as compared with those from a number of machine learning systems. The applicability of the proposed model as a useful data classifier is also demonstrated with a real-world medical data classification problem.