Abstract: Setting up of rural telecentres, popularly referred to as
Common Service Centres (CSCs), are considered one of the initial
forerunners of rural e-Governance initiatives under the Government
of India-s National e-Governance Plan (NeGP). CSCs are
implemented on public-private partnership (PPP) – where State
governments play a major role in facilitating the establishment of
CSCs and investments are made by private companies referred to as
Service Centre Agencies (SCAs). CSC implementation is expected to
help in improving public service delivery in a transparent and
efficient manner. However, there is very little research undertaken to
study the actual impact of CSC implementation at the grassroots
level. This paper addresses the gap by identifying the circumstances,
concerns and expectations from the point-of-view of citizens and
examining the finer aspects of social processes in the context of rural
e-Governance.
Abstract: The modern world is experiencing fundamental and dynamic changes. The transformation of international relations; the end of confrontation and successive overcoming of the Cold War consequences have expanded possible international cooperation. The global nuclear conflict threat has been minimized, while a tendency to establish a unipolar world structure with the U.S. economic and power domination is growing. The current world system of international relations, apparently is secular. However, the religious beliefs of one or another nations play a certain (sometimes a key) role, both in the domestic affairs of the individual countries and in the development of bilateral ties. Political situation in Central Asia has been characterized by new factors such as international terrorism; religious extremism and radicalism; narcotrafficking and illicit arms trade of a global character immediately threaten to peace and political stability in Central Asia. The role and influence of Islamic fundamentalism is increasing; political ethnocentrism and the associated aggravation of inter-ethnic relations, the ambiguity of national interests and objectives of major geo-political groups in the Central Asian region regarding the division the political influence, emerge. This article approaches the following issues: the role of Islam in Central Asia; destabilizing factors in Central Asia; Islamic movements in Central Asia, Western Europe and the United States; the United States, Western Europe and Central Asia: religion, politics, ideology, and the US-Central Asia antiterrorism and religious extremism cooperation.
Abstract: Sensitive and predictive DILI (Drug Induced Liver
Injury) biomarkers are needed in drug R&D to improve early
detection of hepatotoxicity. The discovery of DILI biomarkers that
demonstrate the predictive power to identify individuals at risk to
DILI would represent a major advance in the development of
personalized healthcare approaches. In this healthy volunteer
acetaminophen study (4g/day for 7 days, with 3 monitored nontreatment
days before and 4 after), 450 serum samples from 32
subjects were analyzed using protein profiling by antibody
suspension bead arrays. Multiparallel protein profiles were generated
using a DILI target protein array with 300 antibodies, where the
antibodies were selected based on previous literature findings of
putative DILI biomarkers and a screening process using pre dose
samples from the same cohort. Of the 32 subjects, 16 were found to
develop an elevated ALT value (2Xbaseline, responders). Using the
plasma profiling approach together with multivariate statistical
analysis some novel findings linked to lipid metabolism were found
and more important, endogenous protein profiles in baseline samples
(prior to treatment) with predictive power for ALT elevations were
identified.
Abstract: The aim of this paper is to rank the impact of Object
Oriented(OO) metrics in fault prediction modeling using Artificial
Neural Networks(ANNs). Past studies on empirical validation of
object oriented metrics as fault predictors using ANNs have focused
on the predictive quality of neural networks versus standard
statistical techniques. In this empirical study we turn our attention to
the capability of ANNs in ranking the impact of these explanatory
metrics on fault proneness. In ANNs data analysis approach, there is
no clear method of ranking the impact of individual metrics. Five
ANN based techniques are studied which rank object oriented
metrics in predicting fault proneness of classes. These techniques are
i) overall connection weights method ii) Garson-s method iii) The
partial derivatives methods iv) The Input Perturb method v) the
classical stepwise methods. We develop and evaluate different
prediction models based on the ranking of the metrics by the
individual techniques. The models based on overall connection
weights and partial derivatives methods have been found to be most
accurate.
Abstract: There is lot of work done in prediction of the fault proneness of the software systems. But, it is the severity of the faults that is more important than number of faults existing in the developed system as the major faults matters most for a developer and those major faults needs immediate attention. In this paper, we tried to predict the level of impact of the existing faults in software systems. Neuro-Fuzzy based predictor models is applied NASA-s public domain defect dataset coded in C programming language. As Correlation-based Feature Selection (CFS) evaluates the worth of a subset of attributes by considering the individual predictive ability of each feature along with the degree of redundancy between them. So, CFS is used for the selecting the best metrics that have highly correlated with level of severity of faults. The results are compared with the prediction results of Logistic Models (LMT) that was earlier quoted as the best technique in [17]. The results are recorded in terms of Accuracy, Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). The results show that Neuro-fuzzy based model provide a relatively better prediction accuracy as compared to other models and hence, can be used for the modeling of the level of impact of faults in function based systems.
Abstract: Maize and Indian mustard are significant crops in
semi-arid climate zones of India. Improved water management
requires precise scheduling of irrigation, which in turn requires an
accurate computation of daily crop evapotranspiration (ETc). Daily
crop evapotranspiration comes as a product of reference
evapotranspiration (ET0) and the growth stage specific crop
coefficients modified for daily variation. The first objective of
present study is to develop crop coefficients Kc for Maize and Indian
mustard. The estimated values of Kc for maize at the four crop
growth stages (initial, development, mid-season, and late season) are
0.55, 1.08, 1.25, and 0.75, respectively, and for Indian mustard the Kc
values at the four growth stages are 0.3, 0.6, 1.12, and 0.35,
respectively. The second objective of the study is to compute daily
crop evapotranspiration from ET0 and crop coefficients. Average
daily ETc of maize varied from about 2.5 mm/d in the early growing
period to > 6.5 mm/d at mid season. The peak ETc of maize is 8.3
mm/d and it occurred 64 days after sowing at the reproductive growth
stage when leaf area index was 4.54. In the case of Indian mustard,
average ETc is 1 mm/d at the initial stage, >1.8 mm/d at mid season
and achieves a peak value of 2.12 mm/d on 56 days after sowing.
Improved schedules of irrigation have been simulated based on daily
crop evapo-transpiration and field measured data. Simulation shows a
close match between modeled and field moisture status prevalent
during crop season.
Abstract: Cross sections of As radionuclides in the interaction of natGe with 14-30 MeV protons have been deduced by off-line y-ray spectroscopy to find optimal reaction channels leading to radiotracers for positron emission tomography. The experimental results were compared with the previous results and those estimated by the compound nucleus reaction model.
Abstract: Life is beautiful. But, it is decided by genes, environment and the individual and shattered by the natural and / or the invited problems. Most of the global rural helpless masses are struggling for their survival since; they are neglected in all aspects of life including health. Amidst a countless number of miserable diseases in man, diabetes is becoming a dreaded killer and ramifying the entire globe in a jet speed. Diabetes control continues as a Herculean task to the scientific community and the modern society in the 21st century also. T2DM is not pertaining to any age and it can develop even during the childhood. This multifactorial disease abruptly changes the activities of certain vital biomarkers in the present rural T2DM cases. A remarkable variation in the levels of biomarkers like AST, ALT, GGT, ALP, LDH, HbA1C, C- peptide, fasting sugar, post-prandial sugar, sodium, potassium, BUN, creatinine and insulin show the rampant nature of T2DM in this physically active rural agrarian community.
Abstract: Identity verification of authentic persons by their multiview faces is a real valued problem in machine vision. Multiview faces are having difficulties due to non-linear representation in the feature space. This paper illustrates the usability of the generalization of LDA in the form of canonical covariate for face recognition to multiview faces. In the proposed work, the Gabor filter bank is used to extract facial features that characterized by spatial frequency, spatial locality and orientation. Gabor face representation captures substantial amount of variations of the face instances that often occurs due to illumination, pose and facial expression changes. Convolution of Gabor filter bank to face images of rotated profile views produce Gabor faces with high dimensional features vectors. Canonical covariate is then used to Gabor faces to reduce the high dimensional feature spaces into low dimensional subspaces. Finally, support vector machines are trained with canonical sub-spaces that contain reduced set of features and perform recognition task. The proposed system is evaluated with UMIST face database. The experiment results demonstrate the efficiency and robustness of the proposed system with high recognition rates.
Abstract: There are two types of drought as conceptual drought
and operational drought. The three parameters as the beginning, the
end and the degree of severity of the drought can be identifying in
operational drought by average precipitation in the whole region. One
of the methods classified to measure drought is Reconnaissance
Drought Index (RDI). Evapotranspiration is calculated using
Penman-Monteith method by analyzing thirty nine years prolong
climatic data. The evapotranspiration is then utilized in RDI to
classify normalized and standardized RDI. These RDI classifications
led to what kind of drought faced in Bhavnagar region on 12 month
time scale basis. The comparison between actual drought conditions
and RDI method used to find out drought are also illustrated. It can
be concluded that the index results of drought in a particular year are
same in both methods but having different index values where as
severity remain same.
Abstract: The objective of the present study was to examine the
dose-response relationships between antioxidant parameters and liver
contaminant levels of Kazakhstan light crude oil (KLCO) in albino
rats. The animals were repeatedly exposed, by intraperitoneal
injection, to low dosages (0.5–1.5 ml/kg) of KLCO. Rats exposed to
these doses levels did not show any apparent symptoms of
intoxication. Serum aminotransferases increased significantly
(p
Abstract: Wheat prediction was carried out using different meteorological variables together with agro meteorological indices in Ardebil district for the years 2004-2005 & 2005–2006. On the basis of correlation coefficients, standard error of estimate as well as relative deviation of predicted yield from actual yield using different statistical models, the best subset of agro meteorological indices were selected including daily minimum temperature (Tmin), accumulated difference of maximum & minimum temperatures (TD), growing degree days (GDD), accumulated water vapor pressure deficit (VPD), sunshine hours (SH) & potential evapotranspiration (PET). Yield prediction was done two months in advance before harvesting time which was coincide with commencement of reproductive stage of wheat (5th of June). It revealed that in the final statistical models, 83% of wheat yield variability was accounted for variation in above agro meteorological indices.
Abstract: Malate dehydrogenase-glutamate oxaloacetate
aminotransferase (MDh-GOAT) enzyme complex (the EC) was
isolated and purified from wheat and rise, their some main physicchemical
properties were studied. Michael-s constants of the EC
MDh-GOAT to malate, glutamate and NAD were investigated. This
kinetic results show a high relationship to glutamate. Taking into
account important role of the the EC in catabolism of glutamate – the
central amino acid of a nitric exchange, there is a sharp necessity of
deeper studying of this enzyme complex. Therefore the basic purpose
of the work is studying the basic physical and chemical properties of
this enzyme complex discovered by us, which would be very
important for understanding the mechanisms of reaction catalyzed by
the EC.
Abstract: The soil moisture content is an important property of
the soil. The results of mean weekly gravimetric soil moisture
content, measured for the three soil layers within the A horizon,
showed that it was higher for the top 5 cm over the whole period of
monitoring (15/7/2004 up to 10/11/05) with the variation becoming
greater during winter time. This reflects the pattern of rainfall in
Ireland which is spread over the whole year and shows that light
rainfall events during summer time were compensated by loss
through evapotranspiration, but only in the top 5 cm of soil. This
layer had the highest porosity and highest moisture holding capacity
due to the high content of organic matter. The gravimetric soil
moisture contents of the top 5 cm and the underlying 5-15 and 15-25
cm layers show that bottom site of the Hill Field had higher soil
moisture content than the middle and top sites during the whole
period of monitoring.
Abstract: Study of soil properties like field capacity (F.C.) and permanent wilting point (P.W.P.) play important roles in study of soil moisture retention curve. Although these parameters can be measured directly, their measurement is difficult and expensive. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data. In this investigation, 70 soil samples were collected from different horizons of 15 soil profiles located in the Ziaran region, Qazvin province, Iran. The data set was divided into two subsets for calibration (80%) and testing (20%) of the models and their normality were tested by Kolmogorov-Smirnov method. Both multivariate regression and artificial neural network (ANN) techniques were employed to develop the appropriate PTFs for predicting soil parameters using easily measurable characteristics of clay, silt, O.C, S.P, B.D and CaCO3. The performance of the multivariate regression and ANN models was evaluated using an independent test data set. In order to evaluate the models, root mean square error (RMSE) and R2 were used. The comparison of RSME for two mentioned models showed that the ANN model gives better estimates of F.C and P.W.P than the multivariate regression model. The value of RMSE and R2 derived by ANN model for F.C and P.W.P were (2.35, 0.77) and (2.83, 0.72), respectively. The corresponding values for multivariate regression model were (4.46, 0.68) and (5.21, 0.64), respectively. Results showed that ANN with five neurons in hidden layer had better performance in predicting soil properties than multivariate regression.
Abstract: Biochemical Oxygen Demand (BOD) is a measure of
the oxygen used in bacteria mediated oxidation of organic substances
in water and wastewater. Theoretically an infinite time is required for
complete biochemical oxidation of organic matter, but the
measurement is made over 5-days at 20 0C or 3-days at 27 0C test
period with or without dilution. Researchers have worked to further
reduce the time of measurement.
The objective of this paper is to review advancement made in
BOD measurement primarily to minimize the time and negate the
measurement difficulties. Survey of literature review in four such
techniques namely BOD-BARTTM, Biosensors, Ferricyanidemediated
approach, luminous bacterial immobilized chip method.
Basic principle, method of determination, data validation and their
advantage and disadvantages have been incorporated of each of the
methods.
In the BOD-BARTTM method the time lag is calculated for the
system to change from oxidative to reductive state. BIOSENSORS
are the biological sensing element with a transducer which produces
a signal proportional to the analyte concentration. Microbial species
has its metabolic deficiencies. Co-immobilization of bacteria using
sol-gel biosensor increases the range of substrate. In ferricyanidemediated
approach, ferricyanide has been used as e-acceptor instead
of oxygen. In Luminous bacterial cells-immobilized chip method,
bacterial bioluminescence which is caused by lux genes was
observed. Physiological responses is measured and correlated to
BOD due to reduction or emission.
There is a scope to further probe into the rapid estimation of BOD.
Abstract: The aim of present study was to assess the effect of
glucogenic (G) and lipogenic (L) diets on blood metabolites in
Baloochi lambs. Three rumen cannulated Baloochi sheep were used
as a 3×3 Latin square design with 3 periods (28 days). Experimental
diets were a glucogenic, a lipogenic and a mixture of G and L diets
(50:50). The animals were fed diets consisted of 50% chopped alfalfa
hay and 50% concentrate. Diets were fed once daily ad libitum.
Blood samples were taken from jugular vein before the feeding, 2, 4
and 6 hour post feeding at day 27. Results indicated that β-
hydroxybutyrate (BHBA), glucose, insulin and aspartate
aminotransferase (AST) were not affected by treatments (P > 0.05).
However, lipogenic diet increased significantly activity of Alanine
aminotransferase (ALT) and concentration of non-esterified fatty acid
(NEFA) in blood plasma (P < 0.05)
Abstract: The paper proposes a novel technique for iris
recognition using texture and phase features. Texture features are
extracted on the normalized iris strip using Haar Wavelet while phase
features are obtained using LOG Gabor Wavelet. The matching
scores generated from individual modules are combined using sum of
score technique. The system is tested on database obtained from Bath
University and Indian Institute of Technology Kanpur and is giving
an accuracy of 95.62% and 97.66% respectively. The FAR and FRR
of the combined system is also reduced comparatively.
Abstract: Biochemical investigations were carried out to assess
the effect of different exposure regimes of Kazakhstan crude oil
(KCO) on hepatic antioxidant defense system in albino rats.
Contaminants were delivered under two different dosing regimes,
with all treatments receiving the same total contaminant load by the
end of the exposure period. Rats in regime A injected with KCO
once at a dose of 6 ml/kg bw while in regime B injected multiply at a
dose of 1.5 ml/kg bw on day 1, 3, 5 and 8. Antioxidant biomarkers
were measured in hepatic tissue after 1, 3, 5 and 8 days. Significant
induction was observed in serum aminotransferases (ALT, AST)
(p
Abstract: Importance of software quality is increasing leading to development of new sophisticated techniques, which can be used in constructing models for predicting quality attributes. One such technique is Artificial Neural Network (ANN). This paper examined the application of ANN for software quality prediction using Object- Oriented (OO) metrics. Quality estimation includes estimating maintainability of software. The dependent variable in our study was maintenance effort. The independent variables were principal components of eight OO metrics. The results showed that the Mean Absolute Relative Error (MARE) was 0.265 of ANN model. Thus we found that ANN method was useful in constructing software quality model.