Enhanced Image Detection on an ARM based Embedded System

This paper presents a new technique for thedetection of Integrated Circuits within images of Printed Circuit Boards autonomouslyand without the need to be assisted by CAD data. The technique is a key partof a suite of algorithms targeted for an embedded System On Chip architecturebased on the ARM7 platform for real time detection of PCB images for diagnosticpurposes. The technique has a significant reduction in complexity when comparedto conventional approaches such as the Hough Transform. The reduction in complexitymakes the approach ideal for an embedded vision application suchas the one described in this paper. This paper presents the technique, thetarget embedded architecture and results showing the reduction in complexitywhen compared to a Hough Transform.     

Experimental and mathematical studies of natural convection for solid-salt dissolution in water

The phenomena of natural convection caused by a concentration gradient usually creates currents as a result of buoyancy forces. These forces are formed from the combined effect of a fluid density gradient and the body force (gravitational force). The above phenomenon was studied experimentally in a circular glass column of 0.08 m diameter and 1 m length. This column was erected vertically and filled with distilled water with a salt bag placed on top of it and partially immersed in water. The dissolution mechanism was then modelled and a finite difference method was used to solve the formulated equations by using the implicit scheme of MacCormack (Anderson et al., 1984). The experimental results and the numerical predictions are represented graphically and give compatible agreement.     

A study of neutron and gamma radiation effects on transmission of various types of glasses, optical coatings, cemented optics and fiber

A study of radiation effects on various types of glasses, dielectric optical coatings, cemented optics and fiber was undertaken with a view to select them for extreme radiation environments. Samples were exposed to different radiation doses in the Pakistan Research Reactor-I (PARR-I) for neutron and Cobalt 60 source for gamma irradiation. Transmissions were measured before and after irradiation. The dielectric coatings were subjected to additional tests (adhesion, abrasion and humidity, etc.) as per MIL-M-13508C and MIL-C-675C. All 15 glasses studied showed varying amounts of transmission loss as expected, with negligible degradation for three types. Recovery of transmissions with time/ageing was also studied, with more or less complete recovery with temperature annealing. A faster bleaching of darkened/brown glasses was achieved by using UV lamps or UV laser. The dielectric coatings (HR, AR) and one of the two commercial optical cements showed excellent resistance to neutrons and gamma radiations, and could be good candidates for the fabrication and utilization of optical components in extreme radiation environments. The data allowed several Chinese glasses to be studied for the first time.     

Development of an Expert System for Selection of Dam Type on Alluvium Foundations

. A knowledge-based expert system was developed to aid in the selection of the type of dam. The dam type selector expert system (DTSA ES) was designed to determine the type of dam on the alluvium foundations. Detailed expert knowledge is required to estimate the type of dam and to develop an expert system. The DTSA ES utilizes rules of thumb used by an expert for determining the selection of the type of dam. The DTSA ES was developed using a shell program. The expert system was tested on several dam sites in order to validate the decision obtained. The use of this expert system, containing knowledge about the selection of dam type, can be helpful to students, potential owners or contractors in selecting dam types. The current prototype always needs additional parameters for more detailed analyses of new developments. However, the current DTSA ES is designed to include existing information about dam types.     

Lung nodules detection using semantic segmentation and classification with optimal features

Neural Computing and Applications - Lung cancer is a deadly disease if not diagnosed in its early stages. However, early detection of lung cancer is a challenging task due to the shape and size of...     

Isolation and characterization of cellulose nanowhiskers from Acacia caesia plant

Acacia caesia (L.) Willd (soap bark) fiber is an abundant natural resource, that is rich in cellulose. The study reports the effective utilization of underutilized Acacia caesia fiber for the isolation of nanocellulose whiskers. The nanocellulose whiskers were isolated successfully from Acacia caesia fibers by following alkali, bleaching, and sulfuric acid treatment. The obtained nanocellulose whiskers were carefully investigated for its chemical composition, structure, morphology, crystallinity, and thermal stability. The chemical composition and Fourier transform infrared spectra of nanocellulose whiskers showed the elimination of the non-cellulosic parts present in the raw Acacia caesia fibers. The X-ray diffraction analysis showed an upsurge in the crystallinity of the cellulose fibers after the chemical treatments. The isolation of nanocellulose whiskers from Acacia caesia raw fiber was confirmed by electron microscopy analysis. The thermogravimetric analysis showed remarkably high char residue for the nanocellulose whiskers compared to raw fibers. Based on the properties of nanocellulose whiskers, it can be concluded that the nanocellulose whiskers produced from Acacia caesia raw fibers are potential reinforcing material for developing high-performance green composites.     

A new approach based on a discrete hidden Markov model using the Rocchio algorithm for the diagnosis of heart valve diseases

Abstract: Application of the Doppler ultrasound technique in the diagnosis of heart diseases has been increasing in the last decade since it is non‐invasive, practicable and reliable. In this study, a new approach based on the discrete hidden Markov model (DHMM) is proposed for the diagnosis of heart valve disorders. For the calculation of hidden Markov model (HMM) parameters according to the maximum likelihood approach, HMM parameters belonging to each class are calculated by using training samples that only belong to their own classes. In order to calculate the parameters of DHMMs, not only training samples of the related class but also training samples of other classes are included in the calculation. Therefore HMM parameters that reflect a class's characteristics are more represented than other class parameters. For this aim, the approach was to use a hybrid method by adapting the Rocchio algorithm. The proposed system was used in the classification of the Doppler signals obtained from aortic and mitral heart valves of 215 subjects. The performance of this classification approach was compared with the classification performances in previous studies which used the same data set and the efficiency of the new approach was tested. The total classification accuracy of the proposed approach (95.12%) is higher than the total accuracy rate of standard DHMM (94.31%), continuous HMM (93.5%) and support vector machine (92.67%) classifiers employed in our previous studies and comparable with the performance levels of classifications using artificial neural networks (95.12%) and fuzzy‐C‐means/CHMM (95.12%).     

Prosthetic Hand Finger Control Using Fuzzy Sliding Modes

In order to improve the life quality of amputees, providing approximate manipulation ability of a human hand to that of a prosthetic hand is considered by many researchers. In this study, a biomechanical model of the index finger of the human hand is developed based on the human anatomy. Since the activation of finger bones are carried out by tendons, a tendon configuration of the index finger is introduced and used in the model to imitate the human hand characteristics and functionality. Then, fuzzy sliding mode control where the slope of the sliding surface is tuned by a fuzzy logic unit is proposed and applied to have the finger model to follow a certain trajectory. The trajectory of the finger model, which mimics the motion characteristics of the human hand, is pre-determined from the camera images of a real hand during closing and opening motion. Also, in order to check the robust behaviour of the controller, an unexpected joint friction is induced on the prosthetic finger on its way. Finally, the resultant prosthetic finger motion and the tendon forces produced are given and results are discussed.     

TEM characterization of Ge precipitates in an Al-1.6at% Ge alloy

The growth mechanism and morphology of Ge precipitates in an Al-Ge alloy was characterized by a combination of in-situ transmission electron microscopy, high-resolution transmission electron microscopy and three-dimensional electron tomography. Anisotropic growth of rod-shaped Ge precipitates was observed by in-situ transmission electron microscopy over different time periods, and faceting of the precipitates was clearly seen using high-resolution transmission electron microscopy and three-dimensional electron tomography. This anisotropic growth of rod-shaped Ge precipitates was enhanced by vacancy concentration as proposed previously, but also by surface diffusion as observed during the in-situ experiment. Furthermore, a variety of precipitate morphologies was identified by three-dimensional electron tomography.     

A Novel Contour Tracing Algorithm for Object Shape Reconstruction Using Parametric Curves

Parametric curves such as Bézier and B-splines, originally developed for the design of automobile bodies, are now also used in image processing and computer vision. For example, reconstructing an object shape in an image, including different translations, scales, and orientations, can be performed using these parametric curves. For this, Bézier and B-spline curves can be generated using a point set that belongs to the outer boundary of the object. The resulting object shape can be used in computer vision fields, such as searching and segmentation methods and training machine learning algorithms. The prerequisite for reconstructing the shape with parametric curves is to obtain sequentially the points in the point set. In this study, a novel algorithm has been developed that sequentially obtains the pixel locations constituting the outer boundary of the object. The proposed algorithm, unlike the methods in the literature, is implemented using a filter containing weights and an outer circle surrounding the object. In a binary format image, the starting point of the tracing is determined using the outer circle, and the next tracing movement and the pixel to be labeled as the boundary point is found by the filter weights. Then, control points that define the curve shape are selected by reducing the number of sequential points. Thus, the Bézier and B-spline curve equations describing the shape are obtained using these points. In addition, different translations, scales, and rotations of the object shape are easily provided by changing the positions of the control points. It has also been shown that the missing part of the object can be completed thanks to the parametric curves.