Effect of Boronizing on Operating Stability of Steel AISI 304L under Erosion Impact of Hard Particles

Metal Science and Heat Treatment - The effect of solid boronizing at 950°C for 2 and 4 h on the phase composition, microstructure, hardness and abrasive wear of steel AISI 304L is studied...     

Enhanced antenna-pattern measurements for Satellite systems

This paper describes an enhanced measurement technique for earth-station antennas in a satellite communication system. A new data-acquisition algorithm improves the dynamic range of the measurements by increasing the signal-to-noise ratio in the test setup. The resolution limitation of conventional techniques is eliminated without any modifications to the ground station setup. The proposed approach improves the conventional measurement techniques by utilizing pulse modulation of the test-signal amplitude and its synchronous detection. The noise floor in the pattern is reduced by biasing out the average noise power calculated during the OFF cycle of the pulse. In addition, a randomly fluctuating local mean in the receiver output is reduced. Experimental results show improvements of as much as 25 dB in the noise variance and over 11 dB in the dynamic range of the antenna pattern.     

Fabrication of co-PVDF/modacrylic/SiO2 nanofibrous membrane: Composite separator for safe and high performance lithium-ion batteries

Highly porous free-standing co-poly(vinylidene fluoride)/modacrylic/SiO₂ nanofibrous membrane was developed using electrically-assisted solution blow spinning method. The performance and the potential of the membrane as a lithium-ion battery separator were investigated. The addition of modacrylic enhanced the solution spinnability that resulted in defect-free membranes. Moreover, the presence of modacrylic enhanced the dimensional and thermal stabilities, while the addition of hydrophilic SiO₂ nanoparticle enhanced both mechanical property and ionic conductivity. Combustion test results illustrated that the presence of modacrylic provide flame retarding property over a set of different polymeric-based membranes. Electrochemical performance results showed that the developed membrane can increase the battery capacity compared with the commercial separator.     

The musculoskeletal system complaints of office workers at a vehicle production factory

This study aimed to determine the prevalence of and factors contributing to musculoskeletal system complaints (MSC) in office workers of a vehicle production factory and absenteeism due to these complaints. A total of 86.2% (n = 333) of the workers completed the survey. Of the workers, 73 (21.9%) were women, and 260 (78.1%) were men, and the mean age was 36.9 ± 8.75 years. The majority of the personnel had more than one symptom with a prevalence of 80.8%. The most frequently observed discomfort was tension and pain in the back muscles (58.6%) and in the neck muscles (58.3%), followed by low back pain (41%) and shoulder pain (30.3%). Pain in the shoulders, neck, and the back and pain and numbness in the fingers were statistically significantly more prevalent in employees who spent more than 5 hours per day performing desk work. Furthermore, all of the complaints, excluding pain in the elbows and knees, were statistically significantly more common in the women. When each complaint and the effects of contributing risk factors were analyzed by logistic regression analysis, pain in the shoulders, neck, and back; pain that spread to the arms; and pain in the fingers were correlated with longer work hours and the female gender (p < 0.05). The number of employees who had used sick leave within the past year due to MSCs was 11.7%. In conclusion, duration of work hours, frequency of breaks, and gender were determined as the most important risk factors in computer users regarding MSCs. © 2011 Wiley Periodicals, Inc.     

A semantic backend for content management systems

The users of a content repository express the semantics they have in mind while defining the content items and their properties, and forming them into a particular hierarchy. However, this valuable semantics is not formally expressed, and hence cannot be used to discover meaningful relationships among the content items in an automated way. Although the need is apparent, there are several challenges in explicating this semantics in a fully automated way: first, it is difficult to distinguish between data and the metadata in the repository and secondly, not all the metadata defined, such as the file size or encoding type, contribute to the meaning. More importantly, for the developed solution to have practical value, it must address the constraints of the content management system (CMS) industry: CMS industry cannot change their repositories in production use and they need a generic solution not limited to a specific repository architecture. In this article, we address all these challenges through a set of tools developed which first semi-automatically explicate the content repository semantics to a knowledge-base and establish semantic bridges between this backend knowledge-base and the content repository. The repository content is dynamic; to be able to maintain the content repository semantics while new content is created, the changes in the repository semantics are reflected onto the knowledge-base through the semantic bridges. The tool set is complemented with a search engine that make use of the explicated semantics.     

Colon segmentation and colonic polyp detection using cellular neural networks and three-dimensional template matching

Abstract: In this study, an automatic three-dimensional computer-aided detection system for colonic polyps was developed. Computer-aided detection for computed tomography colonography aims at facilitating the detection of colonic polyps. First, the colon regions of whole computed tomography images were carefully segmented to reduce computational burden and prevent false positive detection. In this process, the colon regions were extracted by using a cellular neural network and then the regions of interest were determined. In order to improve the segmentation performance of the study, weights in the cellular neural network were calculated by three heuristic optimization techniques, namely genetic algorithm, differential evaluation and artificial immune system. Afterwards, a three-dimensional polyp template model was constructed to detect polyps on the segmented regions of interest. At the end of the template matching process, the volumes geometrically similar to the template were emhanced.     

Handling Updates and Crashes in VoD Systems

Though there have been several recent efforts to develop disk based video servers, these approaches have all ignored the topic of updates and disk server crashes. In this paper, we present a priority based model for building video servers that handle two classes of events: user events that could include enter, play, pause, rewind, fast-forward, exit, as well assystem events such as insert, delete, server-down, server-up that correspond to uploading new movie blocks onto the disk(s), eliminating existing blocks from the disk(s), and/or experiencing a disk server crash. We will present algorithms to handle such events. Our algorithms are provably correct, and computable in polynomial time. Furthermore, we guarantee that under certain reasonable conditions, continuing clients experience jitter free presentations. We further justify the efficiency of our techniques with a prototype implementation and experimental results.     

Computationally highly efficient mixture of adaptive filters

We introduce a new combination approach for the mixture of adaptive filters based on the set-membership filtering (SMF) framework. We perform SMF to combine the outputs of several parallel running adaptive algorithms and propose unconstrained, affinely constrained and convexly constrained combination weight configurations. Here, we achieve better trade-off in terms of the transient and steady-state convergence performance while providing significant computational reduction. Hence, through the introduced approaches, we can greatly enhance the convergence performance of the constituent filters with a slight increase in the computational load. In this sense, our approaches are suitable for big data applications where the data should be processed in streams with highly efficient algorithms. In the numerical examples, we demonstrate the superior performance of the proposed approaches over the state of the art using the well-known datasets in the machine learning literature.     

Experimental study of a micro-scale sloped solar chimney power plant

Journal of Mechanical Science and Technology - Solar chimney power plants (SCPP) are structures that have the potential to generate a significant amount of electrical energy without harming the...