Abstract: In this paper we present a noise reduction filter for video processing. It is based on the recently proposed two dimensional steering kernel, extended to three dimensions and further augmented to suit the spatial-temporal domain of video processing. Two alternative filters are proposed - the time symmetric kernel and the time asymmetric kernel. The first reduces the noise on single sequences, but to handle the problems at scene shift the asymmetric kernel is introduced. The performance of both are tested on simulated data and on a real video sequence together with the existing steering kernel. The proposed kernels improves the Rooted Mean Squared Error (RMSE) compared to the original steering kernel method on video material.
Abstract: A new low-voltage floating gate MOSFET (FGMOS)
based squarer using square law characteristic of the FGMOS is
proposed in this paper. The major advantages of the squarer are simplicity,
rail-to-rail input dynamic range, low total harmonic distortion,
and low power consumption. The proposed circuit is biased without
body effect. The circuit is designed and simulated using SPICE in
0.25μm CMOS technology. The squarer is operated at the supply
voltages of ±0.75V . The total harmonic distortion (THD) for the
input signal 0.75Vpp at 25 KHz, and maximum power consumption
were found to be less than 1% and 319μW respectively.
Abstract: One of the long standing challenging aspect in mobile robotics is the ability to navigate autonomously, avoiding modeled and unmodeled obstacles especially in crowded and unpredictably changing environment. A successful way of structuring the navigation task in order to deal with the problem is within behavior based navigation approaches. In this study, Issues of individual behavior design and action coordination of the behaviors will be addressed using fuzzy logic. A layered approach is employed in this work in which a supervision layer based on the context makes a decision as to which behavior(s) to process (activate) rather than processing all behavior(s) and then blending the appropriate ones, as a result time and computational resources are saved.
Abstract: Large scale systems such as computational Grid is
a distributed computing infrastructure that can provide globally
available network resources. The evolution of information processing
systems in Data Grid is characterized by a strong decentralization of
data in several fields whose objective is to ensure the availability and
the reliability of the data in the reason to provide a fault tolerance
and scalability, which cannot be possible only with the use of the
techniques of replication. Unfortunately the use of these techniques
has a height cost, because it is necessary to maintain consistency
between the distributed data. Nevertheless, to agree to live with
certain imperfections can improve the performance of the system by
improving competition. In this paper, we propose a multi-layer protocol
combining the pessimistic and optimistic approaches conceived
for the data consistency maintenance in large scale systems. Our
approach is based on a hierarchical representation model with tree
layers, whose objective is with double vocation, because it initially
makes it possible to reduce response times compared to completely
pessimistic approach and it the second time to improve the quality
of service compared to an optimistic approach.
Abstract: The hot deformation behavior of high strength low
alloy (HSLA) steels with different chemical compositions under hot
working conditions in the temperature range of 900 to 1100℃ and
strain rate range from 0.1 to 10 s-1 has been studied by performing a
series of hot compression tests. The dynamic materials model has been
employed for developing the processing maps, which show variation
of the efficiency of power dissipation with temperature and strain rate.
Also the Kumar-s model has been used for developing the instability
map, which shows variation of the instability for plastic deformation
with temperature and strain rate. The efficiency of power dissipation
increased with decreasing strain rate and increasing temperature in the
steel with higher Cr and Ti content. High efficiency of power
dissipation over 20 % was obtained at a finite strain level of 0.1 under
the conditions of strain rate lower than 1 s-1 and temperature higher
than 1050 ℃ . Plastic instability was expected in the regime of
temperatures lower than 1000 ℃ and strain rate lower than 0.3 s-1. Steel
with lower Cr and Ti contents showed high efficiency of power
dissipation at higher strain rate and lower temperature conditions.
Abstract: Simultaneous effects of temperature, immersion time, salt concentration, sucrose concentration, pressure and convective dryer temperature on the combined osmotic dehydration - convective drying of edible button mushrooms were investigated. Experiments were designed according to Central Composite Design with six factors each at five different levels. Response Surface Methodology (RSM) was used to determine the optimum processing conditions that yield maximum water loss and rehydration ratio and minimum solid gain and shrinkage in osmotic-convective drying of edible button mushrooms. Applying surfaces profiler and contour plots optimum operation conditions were found to be temperature of 39 °C, immersion time of 164 min, salt concentration of 14%, sucrose concentration of 53%, pressure of 600 mbar and drying temperature of 40 °C. At these optimum conditions, water loss, solid gain, rehydration ratio and shrinkage were found to be 63.38 (g/100 g initial sample), 3.17 (g/100 g initial sample), 2.26 and 7.15%, respectively.
Abstract: Dorsal hand vein pattern is an emerging biometric which is attracting the attention of researchers, of late. Research is being carried out on existing techniques in the hope of improving them or finding more efficient ones. In this work, Principle Component Analysis (PCA) , which is a successful method, originally applied on face biometric is being modified using Cholesky decomposition and Lanczos algorithm to extract the dorsal hand vein features. This modified technique decreases the number of computation and hence decreases the processing time. The eigenveins were successfully computed and projected onto the vein space. The system was tested on a database of 200 images and using a threshold value of 0.9 to obtain the False Acceptance Rate (FAR) and False Rejection Rate (FRR). This modified algorithm is desirable when developing biometric security system since it significantly decreases the matching time.
Abstract: Nowadays, hand vein recognition has attracted more attentions in identification biometrics systems. Generally, hand vein image is acquired with low contrast and irregular illumination. Accordingly, if you have a good preprocessing of hand vein image, we can easy extracted the feature extraction even with simple binarization. In this paper, a proposed approach is processed to improve the quality of hand vein image. First, a brief survey on existing methods of enhancement is investigated. Then a Radon Like features method is applied to preprocessing hand vein image. Finally, experiments results show that the proposed method give the better effective and reliable in improving hand vein images.
Abstract: Virtual Assembly (VA) is one of the key technologies
in advanced manufacturing field. It is a promising application of
virtual reality in design and manufacturing field. It has drawn much
interest from industries and research institutes in the last two decades.
This paper describes a process for integrating an interactive Virtual
Reality-based assembly simulation of a digital mockup with the
CAD/CAM infrastructure. The necessary hardware and software
preconditions for the process are explained so that it can easily be
adopted by non VR experts. The article outlines how assembly
simulation can improve the CAD/CAM procedures and structures;
how CAD model preparations have to be carried out and which
virtual environment requirements have to be fulfilled. The issue of
data transfer is also explained in the paper. The other challenges and
requirements like anti-aliasing and collision detection have also been
explained. Finally, a VA simulation has been carried out for a ball
valve assembly and a car door assembly with the help of Vizard
virtual reality toolkit in a semi-immersive environment and their
performance analysis has been done on different workstations to
evaluate the importance of graphical processing unit (GPU) in the
field of VA.
Abstract: We have developed a computer program consisting of
6 subtests assessing the children hand dexterity applicable in the
rehabilitation medicine. We have carried out a normative study on a
representative sample of 285 children aged from 7 to 15 (mean age
11.3) and we have proposed clinical standards for three age groups
(7-9, 9-11, 12-15 years). We have shown statistical significance of
differences among the corresponding mean values of the task time
completion. We have also found a strong correlation between the task
time completion and the age of the subjects, as well as we have
performed the test-retest reliability checks in the sample of 84
children, giving the high values of the Pearson coefficients for the
dominant and non-dominant hand in the range 0.740.97 and
0.620.93, respectively.
A new MATLAB-based programming tool aiming at analysis of
cardiologic RR intervals and blood pressure descriptors, is worked
out, too. For each set of data, ten different parameters are extracted: 2
in time domain, 4 in frequency domain and 4 in Poincaré plot
analysis. In addition twelve different parameters of baroreflex
sensitivity are calculated. All these data sets can be visualized in time
domain together with their power spectra and Poincaré plots. If
available, the respiratory oscillation curves can be also plotted for
comparison. Another application processes biological data obtained
from BLAST analysis.
Abstract: The inherent complexity in nowadays- business
environments is forcing organizations to be attentive to the dynamics
in several fronts. Therefore, the management of technological
innovation is continually faced with uncertainty about the future.
These issues lead to a need for a systemic perspective, able to analyze
the consequences of interactions between different factors. The field
of technology foresight has proposed methods and tools to deal with
this broader perspective. In an attempt to provide a method to analyze
the complex interactions between events in several areas, departing
from the identification of the most strategic competencies, this paper
presents a methodology based on the Delphi method and Quality
Function Deployment. This methodology is applied in a sheet metal
processing equipment manufacturer, as a case study.
Abstract: Experiments have been carried out at the Latvia
University of Agriculture Department of Food Technology. The aim
of this work was to assess the effect of thermal treatment in flexible
retort pouch packaging on the quality of potatoes’ produce during the
storage time. Samples were evaluated immediately after retort
thermal treatment; and following 1; 2; 3 and 4 storage months at the
ambient temperature of +18±2ºC in vacuum packaging from
polyamide/polyethylene (PA/PE) and aluminum/polyethylene
(Al/PE) film pouches with barrier properties. Experimentally the
quality of the potatoes’ produce in dry butter and mushroom
dressings was characterized by measuring pH, hardness, color,
microbiological properties and sensory evaluation. The sterilization
was effective in protecting the produce from physical, chemical, and
microbial quality degradation. According to the study of obtained
data, it can be argued that the selected product processing technology
and packaging materials could be applied to provide the safety and
security during four-month storage period.
Abstract: A sequential decision problem, based on the task ofidentifying the species of trees given acoustic echo data collectedfrom them, is considered with well-known stochastic classifiers,including single and mixture Gaussian models. Echoes are processedwith a preprocessing stage based on a model of mammalian cochlearfiltering, using a new discrete low-pass filter characteristic. Stoppingtime performance of the sequential decision process is evaluated andcompared. It is observed that the new low pass filter processingresults in faster sequential decisions.
Abstract: The objective of this research is to develop an advanced driver assistance system characterized with the functions of lane departure warning (LDW), forward collision warning (FCW) and adaptive front-lighting system (AFS). The system is mainly configured a CCD/CMOS camera to acquire the images of roadway ahead in association with the analysis made by an image-processing unit concerning the lane ahead and the preceding vehicles. The input image captured by a camera is used to recognize the lane and the preceding vehicle positions by image detection and DROI (Dynamic Range of Interesting) algorithms. Therefore, the system is able to issue real-time auditory and visual outputs of warning when a driver is departing the lane or driving too close to approach the preceding vehicle unwittingly so that the danger could be prevented from occurring. During the nighttime, in addition to the foregoing warning functions, the system is able to control the bending light of headlamp to provide an immediate light illumination when making a turn at a curved lane and adjust the level automatically to reduce the lighting interference against the oncoming vehicles driving in the opposite direction by the curvature of lane and the vanishing point estimations. The experimental results show that the integrated vehicle image system is robust to most environments such as the lane detection and preceding vehicle detection average accuracy performances are both above 90 %.
Abstract: Support Vector Machine (SVM) is a statistical
learning tool that was initially developed by Vapnik in 1979 and later
developed to a more complex concept of structural risk minimization
(SRM). SVM is playing an increasing role in applications to
detection problems in various engineering problems, notably in
statistical signal processing, pattern recognition, image analysis, and
communication systems. In this paper, SVM was applied to the
detection of SAR (synthetic aperture radar) images in the presence of
partially developed speckle noise. The simulation was done for single
look and multi-look speckle models to give a complete overlook and
insight to the new proposed model of the SVM-based detector. The
structure of the SVM was derived and applied to real SAR images
and its performance in terms of the mean square error (MSE) metric
was calculated. We showed that the SVM-detected SAR images have
a very low MSE and are of good quality. The quality of the
processed speckled images improved for the multi-look model.
Furthermore, the contrast of the SVM detected images was higher
than that of the original non-noisy images, indicating that the SVM
approach increased the distance between the pixel reflectivity levels
(the detection hypotheses) in the original images.
Abstract: Detection and recognition of the Human Body Composition and extraction their measures (width and length of human body) in images are a major issue in detecting objects and the important field in Image, Signal and Vision Computing in recent years. Finding people and extraction their features in Images are particularly important problem of object recognition, because people can have high variability in the appearance. This variability may be due to the configuration of a person (e.g., standing vs. sitting vs. jogging), the pose (e.g. frontal vs. lateral view), clothing, and variations in illumination. In this study, first, Human Body is being recognized in image then the measures of Human Body extract from the image.
Abstract: This research presents a system for post processing of
data that takes mined flat rules as input and discovers crisp as well as
fuzzy hierarchical structures using Learning Classifier System
approach. Learning Classifier System (LCS) is basically a machine
learning technique that combines evolutionary computing,
reinforcement learning, supervised or unsupervised learning and
heuristics to produce adaptive systems. A LCS learns by interacting
with an environment from which it receives feedback in the form of
numerical reward. Learning is achieved by trying to maximize the
amount of reward received. Crisp description for a concept usually
cannot represent human knowledge completely and practically. In the
proposed Learning Classifier System initial population is constructed
as a random collection of HPR–trees (related production rules) and
crisp / fuzzy hierarchies are evolved. A fuzzy subsumption relation is
suggested for the proposed system and based on Subsumption Matrix
(SM), a suitable fitness function is proposed. Suitable genetic
operators are proposed for the chosen chromosome representation
method. For implementing reinforcement a suitable reward and
punishment scheme is also proposed. Experimental results are
presented to demonstrate the performance of the proposed system.
Abstract: Microwave energy can be used for drying purpose. It is unique process. It is distinctly different from conventional drying process. It is advantageous over conventional drying / heating processes. When microwave energy is used for drying purpose, the process can be accelerated with a better control to achieve uniform heating, more conversion efficiency, selective drying and ultimately improved product quality of the output. Also, less floor space and compact system are the added advantages. Existing low power microwave drying system is to be modified with suitable applicator. Appropriate sensors are to be used to measure parameters like moisture, temperature, weight of sample. Suitable high tech controller is to be used to control microwave power continuously from minimum to maximum. Phase - controller, cycle - controller and PWM - controller are some of the advanced power control techniques. It has been proposed to work on turmeric using high-tech phase controller to control the microwave power conveniently. The drying of turmeric with microwave energy employing phase controller gives better results as formulated in this paper and hence new approach of processing turmeric will open future doors of profit making to allied industries and the farmers.
Abstract: Image segmentation is an important step in image
processing. Major developments in medical imaging allow
physicians to use potent and non-invasive methods in order to
evaluate structures, performance and to diagnose human diseases. In
this study, an active contour was used to extract vessel networks
from color retina images. Automatic analysis of retina vessels
facilitates calculation of arterial index which is required to diagnose
some certain retinopathies.
Abstract: The study area receives a wide variety of wastes
generated by municipalities and the industries like paints and
pigments, metal processing industries, thermal power plants electroprocessing
industries etc. The Physico-chemical and structural
investigation of water from river Pandu indicated high level of
chlorides and calcium which made the water unsuitable for human
use. Algae like Cyclotella fumida, Asterionella Formosa,
Cladophora glomerata, Pediastrum simplex, Scenedesmus bijuga,
Cladophora glomerata were the dominant pollution tolerant species
recorded under these conditions. The sensitive and less abundant
species of algae included Spirogyra sps., Merismopedia sps. The
predominance colonies of Zygnema sps, Phormidium sps,
Mycrocystis aeruginosa, Merismopedia minima, Pandorina morum,
seems to correlate with high organic contents of Pandu river water.
This study assumes significance as some algae can be used as
bioindicators of water pollution and algal floral of a municipal drain
carrying waste effluents from industrial area Kanpur and discharge
them into the river Pandu flowing onto southern outskirts of Kanpur
city.