Abstract: Electro Chemical Discharge Machining (ECDM) is an
emerging hybrid machining process used in precision machining of hard and brittle non-conducting materials. The present paper gives a
critical review on materials machined by ECDM under the prevailing machining conditions; capability indicators of the process are
reported. Some results obtained while performing experiments in micro-channeling on soda lime glass using ECDM are also presented. In these experiments, Tool Wear (TW) and Material Removal (MR)
were studied using design of experiments and L–4 orthogonal array. Experimental results showed that the applied voltage was the most influencing parameter in both MR and TW studies. Field
emission scanning electron microscopy (FESEM) results obtained on the microchannels confirmed the presence of micro-cracks, primarily responsible for MR. Chemical etching was also seen along the edges.
The Energy dispersive spectroscopy (EDS) results were used to detect the elements present in the debris and specimens.
Abstract: Dengue fever is prevalent in Malaysia with numerous
cases including mortality recorded over the years. Public education
on the prevention of the desease through various means has been
carried out besides the enforcement of legal means to eradicate
Aedes mosquitoes, the dengue vector breeding ground. Hence, other
means need to be explored, such as predicting the seasonal peak
period of the dengue outbreak and identifying related climate factors
contributing to the increase in the number of mosquitoes. Simulation
model can be employed for this purpose. In this study, we created a
simulation of system dynamic to predict the spread of dengue
outbreak in Hulu Langat, Selangor Malaysia. The prototype was
developed using STELLA 9.1.2 software. The main data input are
rainfall, temperature and denggue cases. Data analysis from the graph
showed that denggue cases can be predicted accurately using these
two main variables- rainfall and temperature. However, the model
will be further tested over a longer time period to ensure its
accuracy, reliability and efficiency as a prediction tool for dengue
outbreak.
Abstract: In the paper it is questioned whether effective state
social policy provides happiness and social progress. For this purpose
selected correlations between Human Development Index (HDI),
share of public social expenditures in GDP, the Happy Planet Index
(HPI), GDP per capita, and Government Effectiveness are examined
and the results are graphically presented. It is shown how a
government can affect well-being and happiness in different countries
of modern world. Also, it is tested the hypothesis about existence of a
certain optimum of well-being and public social expenditures, which
affect direction of social progress. It is concluded that efficient social
policy and wealth are not the only factors determining human
happiness.
Abstract: Majority of researches conducted on Iranian urban
development plans indicate that they have been almost unsuccessful
in terms of draft, execution and goal achievement. Lack or shortage
of essential statistics and information can be listed as an important
reason of the failure of these plans. Lack of figures and information
has turned into an obvious part of the country-s statistics officials.
This problem has made urban planner themselves to embark on
physical surveys including real estate and land pricing, population
and economic census of the city. Apart from the problems facing
urban developers, the possibility of errors is high in such surveys.
In the present article, applying the interview technique, it has
been mentioned that utilizing multipurpose cadastre system as a land
information system is essential for urban development plans in Iran.
It can minimize or even remove the failures facing urban
development plans.
Abstract: An automatic speech recognition system for the
formal Arabic language is needed. The Quran is the most formal
spoken book in Arabic, it is spoken all over the world. In this
research, an automatic speech recognizer for Quranic based speakerindependent
was developed and tested. The system was developed
based on the tri-phone Hidden Markov Model and Maximum
Likelihood Linear Regression (MLLR). The MLLR computes a set
of transformations which reduces the mismatch between an initial
model set and the adaptation data. It uses the regression class tree, as
well as, estimates a set of linear transformations for the mean and
variance parameters of a Gaussian mixture HMM system. The 30th
Chapter of the Quran, with five of the most famous readers of the
Quran, was used for the training and testing of the data. The chapter
includes about 2000 distinct words. The advantages of using the
Quranic verses as the database in this developed recognizer are the
uniqueness of the words and the high level of orderliness between
verses. The level of accuracy from the tested data ranged 68 to 85%.
Abstract: True integration of multimedia services over wired or
wireless networks increase the productivity and effectiveness in
today-s networks. IP Multimedia Subsystems are Next Generation
Network architecture to provide the multimedia services over fixed
or mobile networks. This paper proposes an extended SIP-based QoS
Management architecture for IMS services over underlying IP access
networks. To guarantee the end-to-end QoS for IMS services in
interconnection backbone, SIP based proxy Modules are introduced
to support the QoS provisioning and to reduce the handoff disruption
time over IP access networks. In our approach these SIP Modules
implement the combination of Diffserv and MPLS QoS mechanisms
to assure the guaranteed QoS for real-time multimedia services. To
guarantee QoS over access networks, SIP Modules make QoS
resource reservations in advance to provide best QoS to IMS users
over heterogeneous networks. To obtain more reliable multimedia
services, our approach allows the use of SCTP protocol over SIP
instead of UDP due to its multi-streaming feature. This architecture
enables QoS provisioning for IMS roaming users to differentiate IMS
network from other common IP networks for transmission of realtime
multimedia services. To validate our approach simulation
models are developed on short scale basis. The results show that our
approach yields comparable performance for efficient delivery of
IMS services over heterogeneous IP access networks.
Abstract: In this paper, we investigate the appearance of the giant component in random subgraphs G(p) of a given large finite graph family Gn = (Vn, En) in which each edge is present independently with probability p. We show that if the graph Gn satisfies a weak isoperimetric inequality and has bounded degree, then the probability p under which G(p) has a giant component of linear order with some constant probability is bounded away from zero and one. In addition, we prove the probability of abnormally large order of the giant component decays exponentially. When a contact graph is modeled as Gn, our result is of special interest in the study of the spread of infectious diseases or the identification of community in various social networks.
Abstract: This paper considers the development of a two-point
predictor-corrector block method for solving delay differential
equations. The formulae are represented in divided difference form
and the algorithm is implemented in variable stepsize variable order
technique. The block method produces two new values at a single
integration step. Numerical results are compared with existing
methods and it is evident that the block method performs very well.
Stability regions of the block method are also investigated.
Abstract: Tensile armour wires provide a flexible pipe's
resistance to longitudinal stresses. Flexible pipe manufacturers need
to know the effect of defects such as scratches and cracks, with
dimensions less than 0.2mm which is the limit of the current nondestructive
detection technology, on the fracture stress and fracture
strain of the wire for quality assurance purposes. Recent research
involving the determination of the fracture strength of cracked wires
employed laboratory testing and classical fracture mechanics
approach using non-standardised fracture mechanics specimens
because standard test specimens could not be manufactured from the
wires owing to their sizes. In this work, the effect of miniature
cracks on the fracture properties of tensile armour wires was
investigated using laboratory and finite element tensile testing
simulations with the phenomenological shear fracture model. The
investigation revealed that the presence of cracks shallower than
0.2mm is worse on the fracture strain of the wire.
Abstract: A concern that researchers usually face in different
applications of Artificial Neural Network (ANN) is determination of
the size of effective domain in time series. In this paper, trial and
error method was used on groundwater depth time series to determine
the size of effective domain in the series in an observation well in
Union County, New Jersey, U.S. different domains of 20, 40, 60, 80,
100, and 120 preceding day were examined and the 80 days was
considered as effective length of the domain. Data sets in different
domains were fed to a Feed Forward Back Propagation ANN with
one hidden layer and the groundwater depths were forecasted. Root
Mean Square Error (RMSE) and the correlation factor (R2) of
estimated and observed groundwater depths for all domains were
determined. In general, groundwater depth forecast improved, as
evidenced by lower RMSEs and higher R2s, when the domain length
increased from 20 to 120. However, 80 days was selected as the
effective domain because the improvement was less than 1% beyond
that. Forecasted ground water depths utilizing measured daily data
(set #1) and data averaged over the effective domain (set #2) were
compared. It was postulated that more accurate nature of measured
daily data was the reason for a better forecast with lower RMSE
(0.1027 m compared to 0.255 m) in set #1. However, the size of input
data in this set was 80 times the size of input data in set #2; a factor
that may increase the computational effort unpredictably. It was
concluded that 80 daily data may be successfully utilized to lower the
size of input data sets considerably, while maintaining the effective
information in the data set.
Abstract: The presence of toxic heavy metals in industrial
effluents is one of the serious threats to the environment. Heavy
metals such as Cadmium, Chromium, Lead, Nickel, Zinc, Mercury,
Copper, Arsenic are found in the effluents of industries such as
foundries, electroplating, petrochemical, battery manufacturing,
tanneries, fertilizer, dying, textiles, metallurgical and metal finishing.
Tremendous increase of industrial copper usage and its presence in
industrial effluents has lead to a growing concern about the fate and
effects of Copper in the environment. Percolation of industrial
effluents through soils leads to contamination of ground water and
soils. The transport of heavy metals and their diffusion into the soils
has therefore, drawn the attention of the researchers.
In this study, an attempt has been made to delineate the
mechanisms of transport and fate of copper in terrestrial
environment. Column studies were conducted using perplex glass
square column of dimension side 15 cm and 1.35 m long. The soil
samples were collected from a natural drain near Mohali (India). The
soil was characterized to be poorly graded sandy loam. The soil was
compacted to the field dry density level of about 1.6 g/cm3. Break
through curves for different depths of the column were plotted. The
results of the column study indicated that the copper has high
tendency to flow in the soils and fewer tendencies to get absorbed on
the soil particles. The t1/2 estimates obtained from the studies can be
used for design copper laden wastewater disposal systems.
Abstract: A novel circuit for generating a signal embedded with
features about data from three sensors is presented. This suggested
circuit is making use of a resistance-to-time converter employing a
bridge amplifier, an integrator and a comparator. The second resistive
sensor (Rz) is transformed into duty cycle. Another bridge with
varying resistor, (Ry) in the feedback of an OP AMP is added in
series to change the amplitude of the resulting signal in a proportional
relationship while keeping the same frequency and duty cycle
representing proportional changes in resistors Rx and Rz already
mentioned. The resultant output signal carries three types of
information embedded as variations of its frequency, duty cycle and
amplitude.
Abstract: As the majority of faults are found in a few of its
modules so there is a need to investigate the modules that are
affected severely as compared to other modules and proper
maintenance need to be done in time especially for the critical
applications. As, Neural networks, which have been already applied
in software engineering applications to build reliability growth
models predict the gross change or reusability metrics. Neural
networks are non-linear sophisticated modeling techniques that are
able to model complex functions. Neural network techniques are
used when exact nature of input and outputs is not known. A key
feature is that they learn the relationship between input and output
through training. In this present work, various Neural Network Based
techniques are explored and comparative analysis is performed for
the prediction of level of need of maintenance by predicting level
severity of faults present in NASA-s public domain defect dataset.
The comparison of different algorithms is made on the basis of Mean
Absolute Error, Root Mean Square Error and Accuracy Values. It is
concluded that Generalized Regression Networks is the best
algorithm for classification of the software components into different
level of severity of impact of the faults. The algorithm can be used to
develop model that can be used for identifying modules that are
heavily affected by the faults.
Abstract: Achievement motivation is believed to promote
giftedness attracting people to invest in many programs to adopt
gifted students providing them with challenging activities.
Intellectual giftedness is founded on the fluid intelligence and
extends to more specific abilities through the growth and inputs from
the achievement motivation. Acknowledging the roles played by the
motivation in the development of giftedness leads to an effective
nurturing of gifted individuals. However, no study has investigated
the direct and indirect effects of the achievement motivation and
fluid intelligence on intellectual giftedness. Thus, this study
investigated the contribution of motivation factors to giftedness
development by conducting tests of fluid intelligence using Cattell
Culture Fair Test (CCFT) and analytical abilities using culture
reduced test items covering problem solving, pattern recognition,
audio-logic, audio-matrices, and artificial language, and self report
questionnaire for the motivational factors. A number of 180 highscoring
students were selected using CCFT from a leading university
in Malaysia. Structural equation modeling was employed using Amos
V.16 to determine the direct and indirect effects of achievement
motivation factors (self confidence, success, perseverance,
competition, autonomy, responsibility, ambition, and locus of
control) on the intellectual giftedness. The findings showed that the
hypothesized model fitted the data, supporting the model postulates
and showed significant and strong direct and indirect effects of the
motivation and fluid intelligence on the intellectual giftedness.
Abstract: Due to the high percentage of induction motors in industrial market, there exist a large opportunity for energy savings. Replacement of working induction motors with more efficient ones can be an important resource for energy savings. A calculation of energy savings and payback periods, as a result of such a replacement, based on nameplate motor efficiency or manufacture-s data can lead to large errors [1]. Efficiency of induction motors (IMs) can be extracted using some procedures that use the no-load test results. In the cases that we must estimate the efficiency on-line, some of these procedures can-t be efficient. In some cases the efficiency estimates using the rating values of the motor, but these procedures can have errors due to the different working condition of the motor. In this paper the efficiency of an IM estimated by using the genetic algorithm. The results are compared with the measured values of the torque and power. The results show smaller errors for this procedure compared with the conventional classical procedures, hence the cost of the equipments is reduced and on-line estimation of the efficiency can be made.
Abstract: In this paper, the application of neural networks to study the design of short-term temperature forecasting (STTF) Systems for Kermanshah city, west of Iran was explored. One important architecture of neural networks named Multi-Layer Perceptron (MLP) to model STTF systems is used. Our study based on MLP was trained and tested using ten years (1996-2006) meteorological data. The results show that MLP network has the minimum forecasting error and can be considered as a good method to model the STTF systems.
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: The recent global financial problem urges government
to play role in stimulating the economy due to the fact that private
sector has little ability to purchase during the recession. A concerned
question is whether the increased government spending crowds out
private consumption and whether it helps stimulate the economy. If
the government spending policy is effective; the private consumption
is expected to increase and can compensate the recent extra
government expense. In this study, the government spending is
categorized into government consumption spending and government
capital spending. The study firstly examines consumer consumption
along the line with the demand function in microeconomic theory.
Three categories of private consumption are used in the study. Those
are food consumption, non food consumption, and services
consumption. The dynamic Almost Ideal Demand System of the three
categories of the private consumption is estimated using the Vector
Error Correction Mechanism model. The estimated model indicates
the substituting effects (negative impacts) of the government
consumption spending on budget shares of private non food
consumption and of the government capital spending on budget share
of private food consumption, respectively. Nevertheless the result
does not necessarily indicate whether the negative effects of changes
in the budget shares of the non food and the food consumption means
fallen total private consumption. Microeconomic consumer demand
analysis clearly indicates changes in component structure of
aggregate expenditure in the economy as a result of the government
spending policy. The macroeconomic concept of aggregate demand
comprising consumption, investment, government spending (the
government consumption spending and the government capital
spending), export, and import are used to estimate for their
relationship using the Vector Error Correction Mechanism model.
The macroeconomic study found no effect of the government capital
spending on either the private consumption or the growth of GDP
while the government consumption spending has negative effect on
the growth of GDP. Therefore no crowding out effect of the
government spending is found on the private consumption but it is
ineffective and even inefficient expenditure as found reducing growth
of the GDP in the context of Thailand.
Abstract: This paper reports the results of an experimental work
conducted to investigate the effect of curing conditions on the
compressive strength of self-compacting geopolymer concrete
prepared by using fly ash as base material and combination of sodium
hydroxide and sodium silicate as alkaline activator. The experiments
were conducted by varying the curing time and curing temperature in
the range of 24-96 hours and 60-90°C respectively. The essential
workability properties of freshly prepared Self-compacting
Geopolymer concrete such as filling ability, passing ability and
segregation resistance were evaluated by using Slump flow,
V-funnel, L-box and J-ring test methods. The fundamental
requirements of high flowability and resistance to segregation as
specified by guidelines on Self-compacting Concrete by EFNARC
were satisfied. Test results indicate that longer curing time and curing
the concrete specimens at higher temperatures result in higher
compressive strength. There was increase in compressive strength
with the increase in curing time; however increase in compressive
strength after 48 hours was not significant. Concrete specimens cured
at 70°C produced the highest compressive strength as compared to
specimens cured at 60°C, 80°C and 90°C.
Abstract: This study was conducted to evaluate factors
regulating groundwater quality in an area with agriculture as main
use. Under this study twelve groundwater samples have been
collected from Padra taluka, Dabhoi taluka and Savli taluka of
Vadodara district. Groundwater samples were chemically analyzed
for major physicochemical parameter in order to understand the
different geochemical processes affecting the groundwater quality.
The analytical results shows higher concentration of total dissolved
solids (16.67%), electrical conductivity (25%) and magnesium
(8.33%) for pre monsoon and total dissolved solids (16.67%),
electrical conductivity (33.3%) and magnesium (8.33%) for post
monsoon which indicates signs of deterioration as per WHO and BIS
standards. On the other hand, 50% groundwater sample is unsuitable
for irrigation purposes based on irrigation quality parameters. The
study revealed that application of fertilizer for agricultural
contributing the higher concentration of ions in aquifer of Vadodara
district.