Abstract: Breast Cancer is the most common malignancy in women and the second leading cause of death for women all over the world. Earlier the detection of cancer, better the treatment. The diagnosis and treatment of the cancer rely on segmentation of Sonoelastographic images. Texture features has not considered for Sonoelastographic segmentation. Sonoelastographic images of 15 patients containing both benign and malignant tumorsare considered for experimentation.The images are enhanced to remove noise in order to improve contrast and emphasize tumor boundary. It is then decomposed into sub-bands using single level Daubechies wavelets varying from single co-efficient to six coefficients. The Grey Level Co-occurrence Matrix (GLCM), Local Binary Pattern (LBP) features are extracted and then selected by ranking it using Sequential Floating Forward Selection (SFFS) technique from each sub-band. The resultant images undergo K-Means clustering and then few post-processing steps to remove the false spots. The tumor boundary is detected from the segmented image. It is proposed that Local Binary Pattern (LBP) from the vertical coefficients of Daubechies wavelet with two coefficients is best suited for segmentation of Sonoelastographic breast images among the wavelet members using one to six coefficients for decomposition. The results are also quantified with the help of an expert radiologist. The proposed work can be used for further diagnostic process to decide if the segmented tumor is benign or malignant.
Abstract: The conventional assessment of human semen is a
highly subjective assessment, with considerable intra- and interlaboratory
variability. Computer-Assisted Sperm Analysis (CASA)
systems provide a rapid and automated assessment of the sperm
characteristics, together with improved standardization and quality
control. However, the outcome of CASA systems is sensitive to the
method of experimentation. While conventional CASA systems use
digital microscopes with phase-contrast accessories, producing
higher contrast images, we have used raw semen samples (no
staining materials) and a regular light microscope, with a digital
camera directly attached to its eyepiece, to insure cost benefits and
simple assembling of the system. However, since the accurate finding
of sperms in the semen image is the first step in the examination and
analysis of the semen, any error in this step can affect the outcome of
the analysis. This article introduces and explains an algorithm for
finding sperms in low contrast images: First, an image enhancement
algorithm is applied to remove extra particles from the image. Then,
the foreground particles (including sperms and round cells) are
segmented form the background. Finally, based on certain features
and criteria, sperms are separated from other cells.
Abstract: Reducing energy consumption of embedded systems requires careful memory management. It has been shown that Scratch- Pad Memories (SPMs) are low size, low cost, efficient (i.e. energy saving) data structures directly managed at the software level. In this paper, the focus is on heuristic methods for SPMs management. A method is efficient if the number of accesses to SPM is as large as possible and if all available space (i.e. bits) is used. A Tabu Search (TS) approach for memory management is proposed which is, to the best of our knowledge, a new original alternative to the best known existing heuristic (BEH). In fact, experimentations performed on benchmarks show that the Tabu Search method is as efficient as BEH (in terms of energy consumption) but BEH requires a sorting which can be computationally expensive for a large amount of data. TS is easy to implement and since no sorting is necessary, unlike BEH, the corresponding sorting time is saved. In addition to that, in a dynamic perspective where the maximum capacity of the SPM is not known in advance, the TS heuristic will perform better than BEH.
Abstract: Textile structures are engineered and fabricated to
meet worldwide structural applications. Nevertheless, research
varying textile structure on natural fibre as composite reinforcement
was found to be very limited. Most of the research is focusing on
short fibre and random discontinuous orientation of the reinforcement
structure. Realizing that natural fibre (NF) composite had been
widely developed to be used as synthetic fibre composite
replacement, this research attempted to examine the influence of
woven and cross-ply laminated structure towards its mechanical
performances. Laminated natural fibre composites were developed
using hand lay-up and vacuum bagging technique. Impact and
flexural strength were investigated as a function of fibre type (coir
and kenaf) and reinforcement structure (imbalanced plain woven,
0°/90° cross-ply and +45°/-45° cross-ply). Multi-level full factorial
design of experiment (DOE) and analysis of variance (ANOVA) was
employed to impart data as to how fibre type and reinforcement
structure parameters affect the mechanical properties of the
composites. This systematic experimentation has led to determination
of significant factors that predominant influences the impact and
flexural properties of the textile composites. It was proven that both
fibre type and reinforcement structure demonstrated significant
difference results. Overall results indicated that coir composite and
woven structure exhibited better impact and flexural strength. Yet,
cross-ply composite structure demonstrated better fracture resistance.
Abstract: Recognition of Indian languages scripts is challenging problems. In Optical Character Recognition [OCR], a character or symbol to be recognized can be machine printed or handwritten characters/numerals. There are several approaches that deal with problem of recognition of numerals/character depending on the type of feature extracted and different way of extracting them. This paper proposes a recognition scheme for handwritten Hindi (devnagiri) numerals; most admired one in Indian subcontinent. Our work focused on a technique in feature extraction i.e. global based approach using end-points information, which is extracted from images of isolated numerals. These feature vectors are fed to neuro-memetic model [18] that has been trained to recognize a Hindi numeral. The archetype of system has been tested on varieties of image of numerals. . In proposed scheme data sets are fed to neuro-memetic algorithm, which identifies the rule with highest fitness value of nearly 100 % & template associates with this rule is nothing but identified numerals. Experimentation result shows that recognition rate is 92-97 % compared to other models.
Abstract: Image restoration involves elimination of noise. Filtering techniques were adopted so far to restore images since last five decades. In this paper, we consider the problem of image restoration degraded by a blur function and corrupted by random noise. A method for reducing additive noise in images by explicit analysis of local image statistics is introduced and compared to other noise reduction methods. The proposed method, which makes use of an a priori noise model, has been evaluated on various types of images. Bayesian based algorithms and technique of image processing have been described and substantiated with experimentation using MATLAB.
Abstract: Massive use of places with strong tourist attraction
with the consequent possibility of losing place-identity produces
harmful effects on cities and their users. In order to mitigate this risk,
areas close to such places can be identified so as to widen the
visitor-s range of action and offer alternative activities integrated
with the main site. The cultural places and appropriate activities can
be identified using a method of analysis and design able to trace the
identity of the places, their characteristics and potential, and to
provide a sustainable improvement. The aim of this work is to
propose PlaceMaker as a method of urban analysis and design which
both detects elements that do not feature in traditional mapping and
which constitute the contemporary identity of the places, and
identifies appropriate project interventions. Two final complex maps
– the first of analysis and the second of design – respectively
represent the identity of places and project interventions. In order to
illustrate the method-s potential; the results of the experimentation
carried out in the Trevi-Pantheon route in Rome and the appropriate
interventions to decongest the area are illustrated.
Abstract: In this paper, an experimentation to enhance the
visibility of hot objects in a thermal image acquired with ordinary
digital camera is reported, after the applications of lowpass and
median filters to suppress the distracting granular noises. The
common thresholding and slicing techniques were used on the
histogram at different gray levels, followed by a subjective
comparative evaluation. The best result came out with the threshold
level 115 and the number of slices 3.
Abstract: The applications on numbers are across-the-board that there is much scope for study. The chic of writing numbers is diverse and comes in a variety of form, size and fonts. Identification of Indian languages scripts is challenging problems. In Optical Character Recognition [OCR], machine printed or handwritten characters/numerals are recognized. There are plentiful approaches that deal with problem of detection of numerals/character depending on the sort of feature extracted and different way of extracting them. This paper proposes a recognition scheme for handwritten Hindi (devnagiri) numerals; most admired one in Indian subcontinent our work focused on a technique in feature extraction i.e. Local-based approach, a method using 16-segment display concept, which is extracted from halftoned images & Binary images of isolated numerals. These feature vectors are fed to neural classifier model that has been trained to recognize a Hindi numeral. The archetype of system has been tested on varieties of image of numerals. Experimentation result shows that recognition rate of halftoned images is 98 % compared to binary images (95%).
Abstract: Clearance in the joints of multibody mechanical
systems such as linkage mechanisms and robots is a main source of
vibration, and noise of the whole system, and wear of the joints
themselves. This clearance is an inevitable matter and cannot be
eliminated, since it allows the relative motion between joint
components and make them assemblage. This paper presents an
experimental verification of the obtained simulation results of a slider
– crank mechanism of one clearance revolute joint. The simulation
results are obtained with the aid of CAD and dynamic simulation
softwares, which is an effective method of simulation multibody
systems with clearance joints and have many advantages. The
comparison between both simulation and experimental results shows
that the simulation results are so close to the experimental ones which
proves the accuracy and efficiency of this method of modeling and
simulation of mechanical systems with clearance joints.
Abstract: The contact width is important design parameter for
optimizing the design of new metal gasket for asbestos substitution
gasket. The contact width is found have relationship with the helium
leak quantity. In the increasing of axial load value, the helium leak
quantity is decreasing and the contact width is increasing. This study
provides validity method using simulation analysis and the result is
compared to experimental using pressure sensitive paper. The results
denote similar trend data between simulation and experimental result.
Final evaluation is determined by helium leak quantity to check
leakage performance of gasket design. Considering the phenomena of
position change on the convex contact, it can be developed the
optimization of gasket design by increasing contact width.
Abstract: This paper investigates how the use of machine learning techniques can significantly predict the three major dimensions of learner-s emotions (pleasure, arousal and dominance) from brainwaves. This study has adopted an experimentation in which participants were exposed to a set of pictures from the International Affective Picture System (IAPS) while their electrical brain activity was recorded with an electroencephalogram (EEG). The pictures were already rated in a previous study via the affective rating system Self-Assessment Manikin (SAM) to assess the three dimensions of pleasure, arousal, and dominance. For each picture, we took the mean of these values for all subjects used in this previous study and associated them to the recorded brainwaves of the participants in our study. Correlation and regression analyses confirmed the hypothesis that brainwave measures could significantly predict emotional dimensions. This can be very useful in the case of impassive, taciturn or disabled learners. Standard classification techniques were used to assess the reliability of the automatic detection of learners- three major dimensions from the brainwaves. We discuss the results and the pertinence of such a method to assess learner-s emotions and integrate it into a brainwavesensing Intelligent Tutoring System.
Abstract: This paper presents the theoretical background and
the real implementation of an automated computer system to
introduce machine vision in flower, fruit and vegetable processing
for recollection, cutting, packaging, classification, or fumigation
tasks. The considerations and implementation issues presented in this
work can be applied to a wide range of varieties of flowers, fruits and
vegetables, although some of them are especially relevant due to the
great amount of units that are manipulated and processed each year
over the world. The computer vision algorithms developed in this
work are shown in detail, and can be easily extended to other
applications. A special attention is given to the electromagnetic
compatibility in order to avoid noisy images. Furthermore, real
experimentation has been carried out in order to validate the
developed application. In particular, the tests show that the method
has good robustness and high success percentage in the object
characterization.
Abstract: Fractional Fourier Transform is a powerful tool,
which is a generalization of the classical Fourier Transform. This
paper provides a mathematical relation relating the span in Fractional
Fourier domain with the amplitude and phase functions of the signal,
which is further used to study the variation of quality factor with
different values of the transform order. It is seen that with the
increase in the number of transients in the signal, the deviation of
average Fractional Fourier span from the frequency bandwidth
increases. Also, with the increase in the transient nature of the signal,
the optimum value of transform order can be estimated based on the
quality factor variation, and this value is found to be very close to
that for which one can obtain the most compact representation. With
the entire mathematical analysis and experimentation, we consolidate
the fact that Fractional Fourier Transform gives more optimal
representations for a number of transform orders than Fourier
transform.
Abstract: Factoring Boolean functions is one of the basic operations in algorithmic logic synthesis. A novel algebraic factorization heuristic for single-output combinatorial logic functions is presented in this paper and is developed based on the set theory paradigm. The impact of factoring is analyzed mainly from a low power design perspective for standard cell based digital designs in this paper. The physical implementation of a number of MCNC/IWLS combinational benchmark functions and sub-functions are compared before and after factoring, based on a simple technology mapping procedure utilizing only standard gate primitives (readily available as standard cells in a technology library) and not cells corresponding to optimized complex logic. The power results were obtained at the gate-level by means of an industry-standard power analysis tool from Synopsys, targeting a 130nm (0.13μm) UMC CMOS library, for the typical case. The wire-loads were inserted automatically and the simulations were performed with maximum input activity. The gate-level simulations demonstrate the advantage of the proposed factoring technique in comparison with other existing methods from a low power perspective, for arbitrary examples. Though the benchmarks experimentation reports mixed results, the mean savings in total power and dynamic power for the factored solution over a non-factored solution were 6.11% and 5.85% respectively. In terms of leakage power, the average savings for the factored forms was significant to the tune of 23.48%. The factored solution is expected to better its non-factored counterpart in terms of the power-delay product as it is well-known that factoring, in general, yields a delay-efficient multi-level solution.
Abstract: In this paper a bank of velocity filters is devised to be
used for isolating a moving object with specific velocity in a sequence of frames. The approach used is a 3-D FFT based experimental procedure without applying any theoretical concept
from velocity filters. Accordingly, velocity filters are built using the
spectral signature of each separate moving object. Experimentation
reveals the capabilities of the constructed filter bank to separate moving objects as far as the amplitude as well as the direction of the
velocity are concerned.
Abstract: In this paper we present a new approach to deal with
image segmentation. The fact that a single segmentation result do not
generally allow a higher level process to take into account all the
elements included in the image has motivated the consideration of
image segmentation as a multiobjective optimization problem. The
proposed algorithm adopts a split/merge strategy that uses the result
of the k-means algorithm as input for a quantum evolutionary
algorithm to establish a set of non-dominated solutions. The
evaluation is made simultaneously according to two distinct features:
intra-region homogeneity and inter-region heterogeneity. The
experimentation of the new approach on natural images has proved
its efficiency and usefulness.
Abstract: The use of hard and brittle material has become
increasingly more extensive in recent years. Therefore processing of
these materials for the parts fabrication has become a challenging
problem. However, it is time-consuming to machine the hard brittle
materials with the traditional metal-cutting technique that uses
abrasive wheels. In addition, the tool would suffer excessive wear as
well. However, if ultrasonic energy is applied to the machining
process and coupled with the use of hard abrasive grits, hard and
brittle materials can be effectively machined. Ultrasonic machining
process is mostly used for the brittle materials. The present research
work has developed models using finite element approach to predict
the mechanical stresses sand strains produced in the tool during
ultrasonic machining process. Also the flow behavior of abrasive
slurry coming out of the nozzle has been studied for simulation using
ANSYS CFX module. The different abrasives of different grit sizes
have been used for the experimentation work.
Abstract: Mining tailings represent a generating source of rich heavy metal material with a potential danger the public health and the environment, since these metals, under certain conditions, can leach and contaminate aqueous systems that serve like supplying potable water sources. The strategy for this work is based on the observation, experimentation and the simulation that can be obtained by binding real answers of the hydrodynamic behavior of metals leached from mining tailings, and the applied mathematics that provides the logical structure to decipher the individual effects of the general physicochemical phenomenon. The case of study presented herein focuses on mining tailings deposits located in Monte San Nicolas, Guanajuato, Mexico, an abandoned mine. This was considered the contamination source that under certain physicochemical conditions can favor the metal leaching, and its transport towards aqueous systems. In addition, the cartography, meteorology, geology and the hydrodynamics and hydrological characteristics of the place, will be helpful in determining the way and the time in which these systems can interact. Preliminary results demonstrated that arsenic presents a great mobility, since this one was identified in several superficial aqueous systems of the micro watershed, as well as in sediments in concentrations that exceed the established maximum limits in the official norms. Also variations in pH and potential oxide-reduction were registered, conditions that favor the presence of different species from this element its solubility and therefore its mobility.
Abstract: Wireless Sensor networks have a wide spectrum of civil and military applications that call for secure communication such as the terrorist tracking, target surveillance in hostile environments. For the secure communication in these application areas, we propose a method for generating a hierarchical key structure for the efficient group key management. In this paper, we apply A* algorithm in generating a hierarchical key structure by considering the history data of the ratio of addition and eviction of sensor nodes in a location where sensor nodes are deployed. Thus generated key tree structure provides an efficient way of managing the group key in terms of energy consumption when addition and eviction event occurs. A* algorithm tries to minimize the number of messages needed for group key management by the history data. The experimentation with the tree shows efficiency of the proposed method.