Corrosion and mechanical behavior of fusion bonded epoxy (FBE) in aqueous media

In recent years there have been many reported cases of corrosion failure in cement concrete pipelines. In the majority of cases, the failures have been attributed to rebar corrosion which is caused by the permeability of chloride from low resistivity soil and subsequent attack on a passive layer on an iron bar in the structure. As a possible alternative to cementitious materials, some organic coatings based on olefin, vinyl or epoxy-based polymers have been considered. However, due to a paucity of data on the behavior of these coatings in aqueous media— particularly product water—the possibility of their application in water transmission systems in the Kingdom has not been fully exploited. This paper deals with the studies carried out on the corrosion and mechanical behavior of fusion bonded epoxy (FBE) coating on steel in aqueous media which include product water, distilled water and saline water. The mechanical testings on coating include adhesion, bending and cathodic disbondment testings. The corrosion studies include immersion testing under static and dynamic conditions, autoclave tests and accelerated (salt-fog) tests. The analysis of results indicates chemical inertness of FBE coating in either of the aforementioned water used during testing, good adhesion and no damage to the coating during bending. Cathodic disbondment tests indicate that FBE coating sustains under cathodic protection (CP) conditions. In general, the results of mechanical and corrosion tests indicate that FBE is a promising material for internal coating on steel in water transmission systems.     

Progressive events in supervisory control and compositional verification

This paper investigates some limitations of the nonblocking property when used for supervisor synthesis in discrete event systems. It is shown that there are cases where synthesis with the nonblocking property gives undesired results. To address such cases, the paper introduces progressive events as a means to specify more precisely how a synthesised supervisor should complete its tasks. The nonblocking property is modified to take progressive events into account, and appropriate methods for verification and synthesis are proposed. Experiments show that progressive events can be used in the analysis of industrial-scale systems, and can expose issues that remain undetected by standard nonblocking verification.     

Studies on chemical resistance of polyesters

Chlorendic anhydride based polyester ( I ,) tetrachlorophthalic anhydride based polyester ( II ), dibromoneopentyl glycol based polyester ( III ,) general purpose polyester ( IV ,) blend of dibromoneopentyl glycol based polyester with general purpose polyester ( V ,) chlorendic anhydride and dibromoneopentyl glycol based polyester ( VI ), and a blend of chlorendic anhydride based polyester and dibromoneopentyl glycol based polyester ( VII ) were prepared and their chemical resistance and moisture absorption studied in various reagents, acid, alkali, and water, at 25 and 65°C. It is found that the polyester ( III ) is the least affected in the presence of the acids. In 20% NaOH, there was a decrease in weight for all polyesters at both the temperatures compared to the control except the polyester ( VII ). Increase in weight of all the polyesters was observed during the absorption of moisture both at 25 and 65°C. The increase was higher at higher temperature. Polyester ( III ) thus shows the least absorption of moisture.     

Effect of AlN addition on the electrical resistivity of pressureless sintered SiC ceramics with B4C and C

The effect of 0–12 wt% AlN addition on the electrical resistivity of SiC ceramics pressureless sintered with 0.7 wt% B₄C and 2.5 wt% C additives was investigated. The elemental analysis of SiC grains revealed a codoping of Al and N in the SiC lattice with a higher N concentration with 1 wt% AlN addition and a higher Al concentration with 12 wt% AlN addition. The electrical resistivity decreased by four orders of magnitude (1.7 × 10⁵ → 8.3 × 10¹ Ω cm) with 1 wt% AlN addition due to the increased carrier density (1.7 × 10¹⁰ → 2.3 × 10¹⁵ cm⁻³) caused by excess N-derived donors. However, subsequent AlN addition (4 → 12 wt%) led to an increase (2.9 × 10³ → 1.2 × 10⁴ Ω‧cm) in electrical resistivity due to (1) increased Al dopants which act as deep acceptors for trapping N-derived carriers causing a decrease in carrier density (2.3 × 10¹⁵ → 5.9 × 10¹³ cm⁻³), (2) the formation of electrically insulating SiC-AlN solid solution, and (3) the presence of electrically insulating AlN grains at the grain boundaries.     

Oxidation and sulfidation behavior of Fe-20Cr-16Ni-4Al-1Y2O3 oxide-dispersion-strengthened alloy

High-temperature oxidation and sulfidation studies were conducted on an oxide-dispersion-strengthened alloy of composition Fe-20Cr-16Ni-4Al-1Y₂O₃. The oxidation studies were conducted in air and low-PO₂ environments over a temperature range of 650–1200°C. Results are also reported on the sulfidation resistance of preformed oxide scales and the influence of reoxidation of preformed sulfide scales. Detailed microstructural results and x-ray diffraction analysis data are presented to substantiate the corrosion behavior of the alloy over the wide range of conditions anticipated in fossil-energy systems. Data are also presented on the corrosion behavior of the alloy in oxygen/sulfur mixed gas atmospheres, and the results are used to compare the corrosion behavior of the present alloy with other chromia- and alumina-forming alloys.     

Adaptive image denoising using cuckoo algorithm

This paper presents a novel denoising approach based on smoothing linear and nonlinear filters combined with an optimization algorithm. The optimization algorithm used was cuckoo search algorithm and is employed to determine the optimal sequence of filters for each kind of noise. Noises that would be eliminated form images using the proposed approach including Gaussian, speckle, and salt and pepper noise. The denoising behaviour of nonlinear filters and wavelet shrinkage threshold methods have also been analysed and compared with the proposed approach. Results show the robustness of the proposed filter when compared with the state-of-the-art methods in terms of peak signal-to-noise ratio and image quality index. Furthermore, a comparative analysis is provided between the said optimization algorithm and the genetic algorithm.     

New Hybrid Access Method for Femtocell through Adjusting QoS

The increasing number of mobile users raises issues about coverage extension in some areas such as rural zones, indoor or underground locations： one of suggestion solution to accommodate this growing of mobile user is femtocell. Femtocell have been attracting considerable attention in mobile communications, it is a small base station that install to improve the indoor coverage of a given cellular and to enhance user＇s capacity. Call admission control and resource allocation infemtocell＇s hybrid mode are an essential performance promotion issue. Developing methods for femtocell utilization is very comparative nowadays. The two major limitations of wireless communication are capacity and range. The main contribution of our paper is developing resource allocation scheme that can manage the femocell resources between subscriber （femtocell user） and non-subscriber （macrocell user in order to maximizing the system utilizations, we provide a mechanism that leads to serve more users by admitting more subscribers basing on adjusting QoS of the connected users.     

Learning to Locate Informative Features for Visual Identification

Object identification is a specialized type of recognition in which the category (e.g. cars) is known and the goal is to recognize an object’s exact identity (e.g. Bob’s BMW). Two special challenges characterize object identification. First, inter-object variation is often small (many cars look alike) and may be dwarfed by illumination or pose changes. Second, there may be many different instances of the category but few or just one positive “training” examples per object instance. Because variation among object instances may be small, a solution must locate possibly subtle object-specific salient features, like a door handle, while avoiding distracting ones such as specular highlights. With just one training example per object instance, however, standard modeling and feature selection techniques cannot be used. We describe an on-line algorithm that takes one image from a known category and builds an efficient “same” versus “different” classification cascade by predicting the most discriminative features for that object instance. Our method not only estimates the saliency and scoring function for each candidate feature, but also models the dependency between features, building an ordered sequence of discriminative features specific to the given image. Learned stopping thresholds make the identifier very efficient. To make this possible, category-specific characteristics are learned automatically in an off-line training procedure from labeled image pairs of the category. Our method, using the same algorithm for both cars and faces, outperforms a wide variety of other methods.     

Transthoracic defibrillation of swine with monophasic and biphasic waveforms

BACKGROUND: Biphasic waveforms have had a favorable impact on internal defibrillation but have seen minimal use in transthoracic defibrillation systems. The purpose of this study was to compare monophasic and biphasic waveforms for transthoracic defibrillation in swine. METHODS AND RESULTS: Three interrelated studies were performed in 19 swine to establish the relative transthoracic defibrillation efficacy of biphasic shock waveforms. In study 1, we measured voltage (V50) and energy (E50) strength-duration curves for monophasic and biphasic truncated exponential waveforms. We then independently examined the effects of phase duration and tilt on biphasic waveform defibrillation with a total waveform duration from study 1 that provided the minimum V50 (study 2) and the minimum E50 (study 3). At each pulse duration tested in study 1, biphasic waveforms defibrillated with significantly less voltage and energy than monophasic waveforms. At a duration of 12 ms, there was a voltage minimum for biphasic waveform defibrillation. At this duration, V50 was 1378 +/- 505 V for the biphasic waveform compared with 2185 +/- 361 V for the monophasic waveform, P = .01. For both monophasic and biphasic waveforms, E50 increased with pulse duration. With a total pulse duration of 12 ms, E50 was 169 +/- 101 J for the biphasic waveform compared with 414 +/- 114 J for the monophasic waveform, P = .003. In study 2, optimization of phase duration and total tilt reduced the defibrillation requirements of the 12-ms "minimum voltage" biphasic waveform to 1284 +/- 187 V and 129 +/- 36 J. In study 3, the 8-ms "minimum energy" biphasic waveform had an E50 of 115 +/- 35 J that was 11% less than the 12-ms biphasic waveform, P = .11; however, voltage requirements of 1476 +/- 239 V were 15% higher, P = .005. CONCLUSIONS: This study demonstrates the superiority of truncated biphasic waveforms over truncated monophasic waveforms for transthoracic defibrillation of swine. Biphasic waveforms should prove as advantageous at reducing voltage and energy requirements for transthoracic defibrillation as they have for internal defibrillation.     

EEG‐based brain source localization using visual stimuli

Electroencephalography (EEG) is widely used in variety of research and clinical applications which includes the localization of active brain sources. Brain source localization provides useful information to understand the brain's behavior and cognitive analysis. Various source localization algorithms have been developed to determine the exact locations of the active brain sources due to which electromagnetic activity is generated in brain. These algorithms are based on digital filtering, 3D imaging, array signal processing and Bayesian approaches. According to the spatial resolution provided, the algorithms are categorized as either low resolution methods or high resolution methods. In this research study, EEG data is collected by providing visual stimulus to healthy subjects. FDM is used for head modelling to solve forward problem. The low‐resolution brain electromagnetic tomography (LORETA) and standardized LORETA (sLORETA) have been used as inverse modelling methods to localize the active regions in the brain during the stimulus provided. The results are produced in the form of MRI images. The tables are also provided to describe the intensity levels for estimated current level for the inverse methods used. The higher current value or intensity level shows the higher electromagnetic activity for a particular source at certain time instant. Thus, the results obtained demonstrate that standardized method which is based on second order Laplacian (sLORETA) in conjunction with finite difference method (FDM) as head modelling technique outperforms other methods in terms of source estimation as it has higher current level and thus, current density (J) for an area as compared to others.