Synthesis and characterization of novel diimide–dinaphthols and resulting poly(urethane–imide)s

Novel diols containing imide groups were prepared via condensation of aromatic dianhydrides with 5‐amino‐1‐naphthol. The diimide–dinaphthols prepared were characterized by conventional methods and used to synthesize new poly(urethane–imide)s (PUIs). All the polymers were characterized and their physical properties, such as solubility, solution viscosity, thermal stability, and thermal behaviour were studied. The polymers obtained showed more thermal stability than typical polyurethanes because of the presence of the imide groups. Copyright © 2003 Society of Chemical Industry     

Real-time processing and compression of DNA microarray images.

In this paper, we present a pipeline architecture specifically designed to process and compress DNA microarray images. Many of the pixilated image generation methods produce one row of the image at a time. This property is fully exploited by the proposed pipeline that takes in one row of the produced image at each clock pulse and performs the necessary image processing steps on it. This will remove the present need for sluggish software routines that are considered a major bottleneck in the microarray technology. Moreover, two different structures are proposed for compressing DNA microarray images. The proposed architecture is proved to be highly modular, scalable, and suited for a standard cell VLSI implementation.     

A quantitative comparison of the effects of modeling approaches on system verification using a controlled challenge problem

Requirements Engineering - To reduce program risks, engineering methods capitalizing on modeling and machine assistance have been extensively investigated within systems engineering (and more...     

Predicting roadheader performance by using artificial neural network

With growing use of roadheaders in the world and its significant role in the successful accomplishment of a tunneling project, it is a necessity to accurately predict performance of this machine in different ground conditions. On the other hand, the existence of some shortcomings in the prediction models has made it necessary to perform more research on the development of the new models. This paper makes an attempt to model the rate of roadheader performance based on the geotechnical and geological site conditions. For achieving the aim, an artificial neural network (ANN), a powerful tool for modeling and recognizing the sophisticated structures involved in data, is employed to model the relationship between the roadheader performance and the parameters influencing the tunneling operations with a high correlation. The database used in modeling is compiled from laboratory studies conducted at Azad University at Science and Research Branch, Tehran, Iran. A model with architecture 4-10-1 trained by back-propagation algorithm is found to be optimum. A multiple variable regression (MVR) analysis is also applied to compare performance of the neural network. The results demonstrate that predictive capability of the ANN model is better than that of the MVR model. It is concluded that roadheader performance could be accurately predicted as a function of unconfined compressive strength, Brazilian tensile strength, rock quality designation, and alpha angle R ² = 0.987. Sensitivity analysis reveals that the most effective parameter on roadheader performance is the unconfined compressive strength.     

HEAT TRANSFER IN A THIN LIQUID FILM IN THE PRESENCE OF AN ELECTRIC FIELD

Heat transfer enhancement in an evaporating thin liquid film utilizing a electric field under isothermal interfacial condition is presented. A new mathematical model subjected to van der Waals attractive forces, capillary pressure, and an electric field is developed to describe the heat transfer enhancement in the evaporating thin liquid film. The effect of the electrostatic field on the curvature of the thin film, evaporative flux, pressure gradient distribution, heat flux, and heat transfer coefficient in the thin film is presented. The results show that applying an electric field can enhance heat transfer in a thin liquid film significantly. In addition, utilizing electric fields on the evaporating film will be a way to expand the extended meniscus region to attain high heat transfer coefficients and high rates of heat flux.     

An adaptive LSB matching steganography based on octonary complexity measure

Adaptive steganography methods tend to increase the security against attacks. Most of adaptive methods use LSB flipping (LSB-F) for embedding part of their algorithms. LSB-F is very much vulnerable against simple steganalysis methods but it allows the adaptive algorithms to be extractable at the receiver side. Use of LSB matching (LSB-M) could increase the security but extraction of data at the receiver is difficult or, in occasions, impossible. There are numerous attacks against LSB-M. In this paper we are proposing an adaptive algorithm which, unlike most adaptive methods, uses LSB-M as its embedding method. The proposed method uses a complexity measure based on a local neighborhood analysis for determination of secure locations of an image. Comparable adaptive methods that use LSB-M suffer from possible changes in the complexity of pixels when embedding is performed. The proposed algorithm is such that when a pixel is categorized as complex at the transmitter and is embedded the receiver will identify it as complex too, and data is correctly retrieved. Better performance of the algorithm is shown by obtaining higher PSNR values for the embedded images with respect to comparable adaptive algorithms. The security of the algorithm against numerous attacks is shown to be higher than LSB-M. Also, it is compared with a recent adaptive method and is proved to be advantageous for most embedding rates.     

Counting eosinophils in bronchoalveolar lavage fluid images with fuzzy methodology

This paper proposes a new fuzzy approach to count eosinophils, as a measure of inflammation, in bronchoalveolar lavage fluid images, provided by digital camera through microscope. We use fuzzy cluster analysis and fuzzy classification algorithm to determine the number of objects in an image. For this purpose, a fuzzy image processing procedure consisting of five main stages is presented. The first stage is pre-highlighting the objects in the images by using an image pre-processing method for enhancement, which is sharpening the image with the Laplaian high pass filter in order to have acceptable contrast in the image. The second stage is segmentation by clustering with fuzzy c-mean algorithm for portioning. In this stage the clustered data are the rough symbols of objects in the image containing noise. In the third step, first, a Gaussian low pass filter is used for noise reduction. Then, a contrast adoption in the image is done by modifying the membership functions in the image [H.R. Tizhoosh, G. Krell, B. Michaelis, Knowledge-based enhancement of megavoltage images in radiation therapy using a hybrid neuro-fuzzy system, Image and Vision Computing 19(July) (2000) 217–233]. Object recognition, the fourth stage, will be done by using fuzzy labeling for the objects in the image, using a fuzzy classification method. The number of labeled images shows the number of eosinophils in an image which is an index for diagnosing inflammation. The last stage is tuning parameters and verification of the system performance by using a feed forward Neural Network.     

A magnetic bead-based DNA extraction and purification microfluidic device

This article introduces a novel magnetic bead-based DNA extraction and purification device using active magnetic mixing approach. Mixing and separation steps are performed using functionalised superparamagnetic beads suspended in cell lysis buffer in a circular chamber that is sandwiched between two external magnetic coils. Non-uniform nature of magnetic field causes temporal and spatial distribution of beads within the chamber. This process efficiently mixes the lysis buffer and whole blood in order to extract DNA from target cells. Functionalized surface of the magnetic beads then attract the exposed DNA molecules. Finally, DNA-attached magnetic beads are attracted to the bottom of the chamber by activating the bottom magnetic coil. DNA molecules are extracted from magnetic beads by washing and re-suspension processes. In this study, a circular PMMA microchamber, 25 μL in volume, 500 μm in depth and 8 mm in diameter was fabricated to purify DNA from spiked bacterial cell cultures into the whole blood sample using Promega Magazorb DNA extraction kit. The lysis efficiency was evaluated using a panel of Gram-positive (Bacillus subtilis) and Gram-negative (Escherichia coli) bacterial cells cultures into the blood sample to achieve approximately 100,000 copy levels inside the chip. Manufacturer’s standard extraction protocol was modified to a more simplified process suitable for chip-based extraction. The lysis step was performed using 5 min incubation at 56 °C followed by 5 min incubation at room temperature for binding process. Temperature rise was generated and maintained by the same external magnetic coils used for active mixing. The yield/purity and recovery levels of the extracted DNA were evaluated using quantitative UV spectrophotometer and real-time PCR assay, respectively. Real-time PCR results indicated efficient chip-based bacterial DNA extraction using modified extraction protocol comparable to the standard bench-top extraction process.     

Globally stable and high-performance Internet congestion control through a computational inspiration from nature

There are many reasons to worry that the current congestion control schemes in the Internet may be reaching its limits. Since the nature is a source of excellent solutions for complex problems, this work attempts to solve the congestion control problem, by adopting some biological principles and mechanisms. The current work proposes that the congestion problem in the Internet can be addressed through an inspiration from the population control tactics in nature. Toward this idea, each flow (W ) in the networ...     

Toward the development of interactive virtual dissection with haptic feedback

Traditional, hands-on dissection of an animal is common practice in many classrooms to aid in the study of anatomy and biology. More specifically, virtual dissection environments have been developed making it possible to study the inner workings of animals without cutting them up. In this paper, we present a novel virtual reality dissection simulator, where a user can dissect an animal (i.e. frog) and its organs using a 3D force feedback haptic device. The simulator uses force feedback as part of a multimodal cue to provide guidance and performance feedback to the user. This paper highlights methodologies which are used for addressing some of the key challenges involved in designing and developing simulators, such as: modelling and mechanics of deformation, collision detection between multiple deformable bodies, and haptic feedback.