Abstract: The rapid pace of technological advancement and its
consequential widening digital divide has resulted in the
marginalization of the disabled especially the communication
challenged. The dearth of suitable technologies for the development
of assistive technologies has served to further marginalize the
communications challenged user population and widen this chasm
even further. Given the varying levels of disability there and its
associated requirement for customized solution based. This paper
explains the use of a Software Development Kits (SDK) for the
bridging of this communications divide through the use of industry
poplar communications SDKs towards identification of requirements
for communications challenged users as well as identification of
appropriate frameworks for future development initiatives.
Abstract: Automatic methods of detecting changes through
satellite imaging are the object of growing interest, especially
beca²use of numerous applications linked to analysis of the Earth’s
surface or the environment (monitoring vegetation, updating maps,
risk management, etc...). This work implemented spatial analysis
techniques by using images with different spatial and spectral
resolutions on different dates. The work was based on the principle
of control charts in order to set the upper and lower limits beyond
which a change would be noted. Later, the a contrario approach was
used. This was done by testing different thresholds for which the
difference calculated between two pixels was significant. Finally,
labeled images were considered, giving a particularly low difference
which meant that the number of “false changes” could be estimated
according to a given limit.
Abstract: Many high-risk pathogens that cause disease in
humans are transmitted through various food items. Food-borne
disease constitutes a major public health problem. Assessment of the
quality and safety of foods is important in human health. Rapid and
easy detection of pathogenic organisms will facilitate precautionary
measures to maintain healthy food. The Polymerase Chain Reaction
(PCR) is a handy tool for rapid detection of low numbers of bacteria.
We have designed gene specific primers for most common food
borne pathogens such as Staphylococci, Salmonella and E.coli.
Bacteria were isolated from food samples of various food outlets and
identified using gene specific PCRs. We identified Staphylococci,
Salmonella and E.coli O157 using gene specific primers by rapid and
direct PCR technique in various food samples. This study helps us in
getting a complete picture of the various pathogens that threaten to
cause and spread food borne diseases and it would also enable
establishment of a routine procedure and methodology for rapid
identification of food borne bacteria using the rapid technique of
direct PCR. This study will also enable us to judge the efficiency of
present food safety steps taken by food manufacturers and exporters.
Abstract: The study identified the sources of production
inefficiency of the farming sector in district Faisalabad in the Punjab
province of Pakistan. Data Envelopment Analysis (DEA) technique
was utilized at farm level survey data of 300 farmers for the year
2009. The overall mean efficiency score was 0.78 indicating 22
percent inefficiency of the sample farmers. Computed efficiency
scores were then regressed on farm specific variables using Tobit
regression analysis. Farming experience, education, access to
farming credit, herd size and number of cultivation practices showed
constructive and significant effect on the farmer-s technical
efficiency.
Abstract: This research was to study a comparison of inspector-s performance between regular and complex visual inspection task. Visual task was simulated on DVD read control circuit. Inspection task was performed by using computer. Subjects were 10 undergraduate randomly selected and test for 20/20. Then, subjects were divided into two groups, five for regular inspection (control group) and five for complex inspection (treatment group) tasks. Result was showed that performance on regular and complex inspectors was significantly difference at the level of 0.05. Inspector performance on regular inspection was showed high percentage on defects detected by using equal time to complex inspection. This would be indicated that inspector performance was affected by visual inspection task.
Abstract: A recent neurospiking coding scheme for feature extraction from biosonar echoes of various plants is examined with avariety of stochastic classifiers. Feature vectors derived are employedin well-known stochastic classifiers, including nearest-neighborhood,single Gaussian and a Gaussian mixture with EM optimization.Classifiers' performances are evaluated by using cross-validation and bootstrapping techniques. It is shown that the various classifers perform equivalently and that the modified preprocessing configuration yields considerably improved results.
Abstract: Uranium mining and processing in Brazil occur in a
northeastern area near to Caetité-BA. Several Non-Governmental
Organizations claim that uranium mining in this region is a pollutant
causing health risks to the local population,but those in charge of the
complex extraction and production of“yellow cake" for generating
fuel to the nuclear power plants reject these allegations. This study
aimed at identifying potential problems caused by mining to the
population of Caetité. In this, work,the concentrations of 238U, 232Th
and 40K radioisotopes in the teeth of the Caetité population were
determined by ICP-MS. Teeth are used as bioindicators of
incorporated radionuclides. Cumulative radiation doses in the
skeleton were also determined. The concentration values were below
0.008 ppm, and annual effective dose due to radioisotopes are below
to the reference values. Therefore, it is not possible to state that the
mining process in Caetité increases pollution or radiation exposure in
a meaningful way.
Abstract: In this research, effort was made to identify and
evaluate barriers to the development of entrepreneurship among
Iranian entrepreneur women who were graduated from universities.
In this study, perspectives of thirty-seven available entrepreneur
women were examined. In order to prepare questionnaires and
receive knowledge about barriers among these women, seven cases of
entrepreneur women took part in in-depth interviews. Then, to
evaluate the importance of barriers, the researchers made a
questionnaire with closed questions in which the barriers were
classified into the following categories: personal-familial barriers;
socio-cultural barriers; economic-financial-commercial barriers; and
structural barriers. Entrepreneur women were requested to rate the
importance of each item. The results indicated that there were
different obstacles among entrepreneur women. The order of the
important barriers was as fallow: economic-financial-commercial,
structural, socio-cultural, and personal-familial.
Abstract: Since 2008 a new economic crisis is present is the
entire planet. This crisis affects several domains of the economic but
also of the social life. Consumption decreases due to the lack of
necessary resources of households to increase their expenditures. The
car manufacturing is one of the main industrial activities in European
Union (EU) and the present crisis particularly affects it. The present
study examines the correlations between several socio-economic
indicators and car market in European Union. The target is to find out
the impact of the present economic crisis on the car market in EU.
Abstract: Data mining incorporates a group of statistical
methods used to analyze a set of information, or a data set. It operates
with models and algorithms, which are powerful tools with the great
potential. They can help people to understand the patterns in certain
chunk of information so it is obvious that the data mining tools have
a wide area of applications. For example in the theoretical chemistry
data mining tools can be used to predict moleculeproperties or
improve computer-assisted drug design. Classification analysis is one
of the major data mining methodologies. The aim of thecontribution
is to create a classification model, which would be able to deal with a
huge data set with high accuracy. For this purpose logistic regression,
Bayesian logistic regression and random forest models were built
using R software. TheBayesian logistic regression in Latent GOLD
software was created as well. These classification methods belong to
supervised learning methods.
It was necessary to reduce data matrix dimension before construct
models and thus the factor analysis (FA) was used. Those models
were applied to predict the biological activity of molecules, potential
new drug candidates.
Abstract: Particle detection in very noisy and low contrast images
is an active field of research in image processing. In this article, a
method is proposed for the efficient detection and sizing of subsurface
spherical particles, which is used for the processing of softly fused
Au nanoparticles. Transmission Electron Microscopy is used for
imaging the nanoparticles, and the proposed algorithm has been
tested with the two-dimensional projected TEM images obtained.
Results are compared with the data obtained by transmission optical
spectroscopy, as well as with conventional circular object detection
algorithms.
Abstract: This paper covers various aspects of the Internet film
piracy. In order to successfully deal with this matter, it is needed to
recognize and explain various motivational factors related to film
piracy. Thus, this study proposes groups of economical, sociopsychological
and other factors that could motivate individuals
to engage in pirate activities. The paper also studies the interactions
between downloaders and uploaders and offers the causality of the
motivational factors and its effects on the film industry.
Moreover, the study also focuses on proposed scheme of relations
of downloading movies and the possible effect on box office
revenues.
Abstract: Unified Speech Audio Coding (USAC), the latest MPEG standardization for unified speech and audio coding, uses a speech/audio classification algorithm to distinguish speech and audio segments of the input signal. The quality of the recovered audio can be increased by well-designed orchestra/percussion classification and subsequent processing. However, owing to the shortcoming of the system, introducing an orchestra/percussion classification and modifying subsequent processing can enormously increase the quality of the recovered audio. This paper proposes an orchestra/percussion classification algorithm for the USAC system which only extracts 3 scales of Mel-Frequency Cepstral Coefficients (MFCCs) rather than traditional 13 scales of MFCCs and use Iterative Dichotomiser 3 (ID3) Decision Tree rather than other complex learning method, thus the proposed algorithm has lower computing complexity than most existing algorithms. Considering that frequent changing of attributes may lead to quality loss of the recovered audio signal, this paper also design a modified subsequent process to help the whole classification system reach an accurate rate as high as 97% which is comparable to classical 99%.
Abstract: A new genetic algorithm, termed the 'optimum individual monogenetic genetic algorithm' (OIMGA), is presented whose properties have been deliberately designed to be well suited to hardware implementation. Specific design criteria were to ensure fast access to the individuals in the population, to keep the required silicon area for hardware implementation to a minimum and to incorporate flexibility in the structure for the targeting of a range of applications. The first two criteria are met by retaining only the current optimum individual, thereby guaranteeing a small memory requirement that can easily be stored in fast on-chip memory. Also, OIMGA can be easily reconfigured to allow the investigation of problems that normally warrant either large GA populations or individuals many genes in length. Local convergence is achieved in OIMGA by retaining elite individuals, while population diversity is ensured by continually searching for the best individuals in fresh regions of the search space. The results given in this paper demonstrate that both the performance of OIMGA and its convergence time are superior to those of a range of existing hardware GA implementations.
Abstract: Diffuse viral encephalitis may lack fever and other cardinal signs of infection and hence its distinction from other acute encephalopathic illnesses is challenging. Often, the EEG changes seen routinely are nonspecific and reflect diffuse encephalopathic changes only. The aim of this study was to use nonlinear dynamic mathematical techniques for analyzing the EEG data in order to look for any characteristic diagnostic patterns in diffuse forms of encephalitis.It was diagnosed on clinical, imaging and cerebrospinal fluid criteria in three young male patients. Metabolic and toxic encephalopathies were ruled out through appropriate investigations. Digital EEGs were done on the 3rd to 5th day of onset. The digital EEGs of 5 male and 5 female age and sex matched healthy volunteers served as controls.Two sample t-test indicated that there was no statistically significant difference between the average values in amplitude between the two groups. However, the standard deviation (or variance) of the EEG signals at FP1-F7 and FP2-F8 are significantly higher for the patients than the normal subjects. The regularisation dimension is significantly less for the patients (average between 1.24-1.43) when compared to the normal persons (average between 1.41-1.63) for the EEG signals from all locations except for the Fz-Cz signal. Similarly the wavelet dimension is significantly less (P = 0.05*) for the patients (1.122) when compared to the normal person (1.458). EEGs are subdued in the case of the patients with presence of uniform patterns, manifested in the values of regularisation and wavelet dimensions, when compared to the normal person, indicating a decrease in chaotic nature.
Abstract: Spent petroleum catalyst from Korean petrochemical
industry contains trace amount of metals such as Ni, V and Mo.
Therefore an attempt was made to recover those trace metal using
bioleaching process. Different leaching parameters such as Fe(II)
concentration, pulp density, pH, temperature and particle size of
spent catalyst particle were studied to evaluate their effects on the
leaching efficiency. All the three metal ions like Ni, V and Mo
followed dual kinetics, i.e., initial faster followed by slower rate. The
percentage of leaching efficiency of Ni and V were higher than Mo.
The leaching process followed a diffusion controlled model and the
product layer was observed to be impervious due to formation of
ammonium jarosite (NH4)Fe3(SO4)2(OH)6. In addition, the lower
leaching efficiency of Mo was observed due to a hydrophobic coating
of elemental sulfur over Mo matrix in the spent catalyst.
Abstract: Terminal localization for indoor Wireless Local Area
Networks (WLANs) is critical for the deployment of location-aware
computing inside of buildings. A major challenge is obtaining high
localization accuracy in presence of fluctuations of the received signal
strength (RSS) measurements caused by multipath fading. This paper
focuses on reducing the effect of the distance-varying noise by spatial
filtering of the measured RSS. Two different survey point geometries
are tested with the noise reduction technique: survey points arranged
in sets of clusters and survey points uniformly distributed over the
network area. The results show that the location accuracy improves
by 16% when the filter is used and by 18% when the filter is applied
to a clustered survey set as opposed to a straight-line survey set.
The estimated locations are within 2 m of the true location, which
indicates that clustering the survey points provides better localization
accuracy due to superior noise removal.
Abstract: Human-related information security breaches within organizations are primarily caused by employees who have not been made aware of the importance of protecting the information they work with. Information security awareness is accordingly attracting more attention from industry, because stakeholders are held accountable for the information with which they work. The authors developed an Information Security Retrieval and Awareness model – entitled “ISRA" – that is tailored specifically towards enhancing information security awareness in industry amongst all users of information, to address shortcomings in existing information security awareness models. This paper is principally aimed at expounding a prototype for the ISRA model to highlight the advantages of utilizing the model. The prototype will focus on the non-technical, humanrelated information security issues in industry. The prototype will ensure that all stakeholders in an organization are part of an information security awareness process, and that these stakeholders are able to retrieve specific information related to information security issues relevant to their job category, preventing them from being overburdened with redundant information.
Abstract: The concentrations of aliphatic and polycyclic aromatic hydrocarbons (PAH) were determined in atmospheric aerosol samples collected at a rural site in Hungary (K-puszta, summer 2008), a boreal forest (Hyytiälä,
April 2007) and a polluted rural area in Italy (San Pietro Capofiume, Po Valley, April 2008). A clear distinction between “clean" and “polluted" periods was observed. Concentrations obtained for Hyytiälä are significantly lower than those for the other two sites. Source reconciliation was performed using diagnostic parameters, such as the carbon preference index and ratios between PAH. The presence of an unresolved complex mixture of hydrocarbons, especially for the Finnish and Italian samples, is indicative of petrogenic inputs. In K-puszta, the aliphatic hydrocarbons are dominated by leaf wax n-alkanes. The long range transport of anthropogenic pollution contributed to the Finnish aerosol. Industrial activities and vehicular emissions represent major sources in San Pietro Capofiume. PAH in K-puszta consist of both pyrogenic and petrogenic compounds.
Abstract: An application of the highly biosensor based on pH-sensitive field immobilized urease for urea analysis was demo The main analytical characteristics of the bios determined; the conditions of urea measureme blood were optimized. A conceptual possibility biosensor for detection of urea concentratio patients suffering from renal insufficiency was sensitive and selective effect transistor and monstrated in this work. iosensor developed were ment in real samples of ility of application of the tion in blood serum of as shown.