Abstract: Many non-conventional adsorbent have been studied
as economic alternative to commercial activated carbon and mostly
agricultural waste have been introduced such as rubber leaf powder
and hazelnut shell. Microwave Incinerated Rice Husk Ash
(MIRHA), produced from the rice husk is one of the low-cost
materials that were used as adsorbent of heavy metal. The aim of
this research was to study the feasibility of using MIRHA500 and
MIRHA800 as adsorbent for the removal of Cu(II) metal ions from
aqueous solutions by the batch studies. The adsorption of Cu(II) into
MIRHA500 and MIRH800 favors Fruendlich isotherm and imply
pseudo – kinetic second order which applied chemisorptions
Abstract: Automatic reading of handwritten cheque is a computationally
complex process and it plays an important role in financial
risk management. Machine vision and learning provide a viable
solution to this problem. Research effort has mostly been focused
on recognizing diverse pitches of cheques and demand drafts with an
identical outline. However most of these methods employ templatematching
to localize the pitches and such schemes could potentially
fail when applied to different types of outline maintained by the
bank. In this paper, the so-called outline problem is resolved by
a cheque information tree (CIT), which generalizes the localizing
method to extract active-region-of-entities. In addition, the weight
based density plot (WBDP) is performed to isolate text entities and
read complete pitches. Recognition is based on texture features using
neural classifiers. Legal amount is subsequently recognized by both
texture and perceptual features. A post-processing phase is invoked
to detect the incorrect readings by Type-2 grammar using the Turing
machine. The performance of the proposed system was evaluated
using cheque and demand drafts of 22 different banks. The test data
consists of a collection of 1540 leafs obtained from 10 different
account holders from each bank. Results show that this approach
can easily be deployed without significant design amendments.
Abstract: Intelligent deep-drawing is an instrumental research field in sheet metal forming. A set of 28 different experimental data have been employed in this paper, investigating the roles of die radius, punch radius, friction coefficients and drawing ratios for axisymmetric workpieces deep drawing. This paper focuses an evolutionary neural network, specifically, error back propagation in collaboration with genetic algorithm. The neural network encompasses a number of different functional nodes defined through the established principles. The input parameters, i.e., punch radii, die radii, friction coefficients and drawing ratios are set to the network; thereafter, the material outputs at two critical points are accurately calculated. The output of the network is used to establish the best parameters leading to the most uniform thickness in the product via the genetic algorithm. This research achieved satisfactory results based on demonstration of neural networks.
Abstract: Salinity level may affect early development of
biofuel feedstock crops. The biofuel feedstock crops canola
(Brassica napus L.), sorghum [Sorghum bicolor (L.) Moench], and
sunflower (Helianthus annuus L.); and the potential feedstock crop
sweet corn (Zea mays L.) were planted in media in pots and treated
with aqueous solutions of 0, 0.1, 0.5 and 1.0 M NaCl once at: 1)
planting; 2) 7-10 days after planting or 3) first true leaf expansion.
An additional treatment (4) comprised of one-half strength of the 0.1,
0.5 and 1.0 M (concentrations 0.05, 0.25, 0.5 M at each application)
was applied at first true leaf expansion and four days later. Survival
of most crops decreased below 90% above 0.5 M; survival of canola
decreased above 0.1 M. Application timing had little effect on crop
survival. For canola root fresh and dry weights improved when
application was at plant emergence; for sorghum top and root fresh
weights improved when the split application was used. When
application was at planting root dry weight was improved over most
other applications. Sunflower top fresh weight was among the
highest when saline solutions were split and top dry weight was
among the highest when application was at plant emergence. Sweet
corn root fresh weight was improved when the split application was
used or application was at planting. Sweet corn root dry weight was
highest when application was at planting or plant emergence. Even at
high salinity rates survival rates greater than what might be expected
occurred. Plants that survived appear to be able to adjust to saline
during the early stages of development.
Abstract: An ethnobotanical study was conducted to document
local knowledge and potentials of wild edible tubers that has been
reported and sighted and to investigate and record their distribution in
Pulau Redang and nearby islands of Terengganu, Malaysia.
Information was gathered from 42 villagers by using semi-structured
questionnaire. These respondents were selected randomly and no
appointment was made prior to the visits. For distribution, the
locations of wild edible tubers were recorded by using the Global
Positioning System (GPS). The wild edible tubers recorded were ubi
gadung, ubi toyo, ubi kasu, ubi jaga, ubi seratus and ubi kertas.
Dioscorea or commonly known as yam is reported to be one of the
major food sources worldwide. The majority of villagers used
Dioscorea hispida Dennst. or ubi gadung in many ways in their life
such as for food, medicinal purposes and fish poison. The villagers
have identified this ubi gadung by looking at the morphological
characteristics; that include leaf shape, stem and the color of the
tuber-s flesh.
Abstract: This study investigated the ecological effects of
particulate pollution from a cement factory on the vegetation in the
western Mediterranean coastal desert of Egypt. Variations in
vegetation, soil chemical characters, and some responses of Atriplex
halimus, as a dominant species in the study area, were investigated in
some sites located in different directions from the cement factory
between Burg El-Arab in the east and El-Hammam in the west. The
results showed an obvious decrease in vegetation diversity, in
response to cement-kiln dust pollution, that accompanied by a high
dominance attributed to the high contribution of Atriplex halimus.
Annual species were found to be more sensitive to cement dust
pollution as they all failed to persist in highly disturbed sites. It is
remarkable that cover and phytomass of Atriplex halimus were
increased greatly in response to cement dust pollution, and this was
accompanied by a reduction in the mature seeds and leaf-area of the
plant. The few seeds of the affected individuals seemed to be more
fertile and attained higher germination percentages and exhibited
hardening against drought stress.
Abstract: Sign language is used by the deaf and hard of hearing people for communication. Automatic sign language recognition is a challenging research area since sign language often is the only way of communication for the deaf people. Sign language includes different components of visual actions made by the signer using the hands, the face, and the torso, to convey his/her meaning. To use different aspects of signs, we combine the different groups of features which have been extracted from the image frames recorded directly by a stationary camera. We combine the features in two levels by employing three techniques. At the feature level, an early feature combination can be performed by concatenating and weighting different feature groups, or by concatenating feature groups over time and using LDA to choose the most discriminant elements. At the model level, a late fusion of differently trained models can be carried out by a log-linear model combination. In this paper, we investigate these three combination techniques in an automatic sign language recognition system and show that the recognition rate can be significantly improved.
Abstract: This paper deals with automatic sentence modality
recognition in French. In this work, only prosodic features are
considered. The sentences are recognized according to the three
following modalities: declarative, interrogative and exclamatory
sentences. This information will be used to animate a talking head for
deaf and hearing-impaired children. We first statistically study a real
radio corpus in order to assess the feasibility of the automatic
modeling of sentence types. Then, we test two sets of prosodic
features as well as two different classifiers and their combination. We
further focus our attention on questions recognition, as this modality
is certainly the most important one for the target application.
Abstract: To maximise furnace production it-s necessary to
optimise furnace control, with the objectives of achieving maximum
power input into the melting process, minimum network distortion
and power-off time, without compromise on quality and safety. This
can be achieved with on the one hand by an appropriate electrode
control and on the other hand by a minimum of AC transformer
switching.
Electrical arc is a stochastic process; witch is the principal cause
of power quality problems, including voltages dips, harmonic
distortion, unbalance loads and flicker. So it is difficult to make an
appropriate model for an Electrical Arc Furnace (EAF). The factors
that effect EAF operation are the melting or refining materials,
melting stage, electrode position (arc length), electrode arm control
and short circuit power of the feeder. So arc voltages, current and
power are defined as a nonlinear function of the arc length. In this
article we propose our own empirical function of the EAF and model,
for the mean stages of the melting process, thanks to the
measurements in the steel factory.
Abstract: The curves, of which the square of the distance
between the two points equal to zero, are called minimal or isotropic
curves [4]. In this work, first, necessary and sufficient conditions to
be a Pseudo Helix, which is a special case of such curves, are
presented. Thereafter, it is proven that an isotropic curve-s position
vector and pseudo curvature satisfy a vector differential equation of
fourth order. Additionally, In view of solution of mentioned
equation, position vector of pseudo helices is obtained.
Abstract: In this study, an experimental investigation was carried
out to fix CO2 into the electronic arc furnace (EAF) reducing slag from
stainless steelmaking process under wet grinding. The slag was ground
by the vibrating ball mill with the CO2 and pure water. The reaction
behavior was monitored with constant pressure method, and the
change of CO2 volume in the experimental system with grinding time
was measured. It was found that the CO2 absorption occurred as soon
as the grinding started. The CO2 absorption under wet grinding was
significantly larger than that under dry grinding. Generally, the
amount of CO2 absorption increased as the amount of water, the
amount of slag, the diameter of alumina ball and the initial pressure of
CO2 increased. However, the initial absorption rate was scarcely
influenced by the experimental conditions except for the initial CO2
pressure. According to this research, the CO2 reacted with the CaO
inside the slag to form CaCO3.
Abstract: Stevia rebaudiana Bertoni (natural sweetener) belongs
to Asteraceae family and can be used as substitute of artificial
sweeteners for diabetic patients. Conventionally, it is cultivated by
seeds or stem cutting, but seed viability rate is poor. A protocol for
callus induction and multiplication was developed to produce large
no. of calli in short period. Surface sterilized nodal, leaf and root
explants were cultured on Murashige and Skoog (MS) medium with
different concentrations of plant hormone like, IBA, kinetin, NAA,
2,4-D, and NAA in combination with 2,4-D. 100% callusing was
observed from leaf explants cultured on combination of NAA and
2,4-D after three weeks while with 2,4-D, only 10% callusing was
observed. Calli obtained from leaf and root explants were shiny green
while with nodal explants it was hard and brown. The present
findings deal with induction of callusing in Stevia to achieve the
rapid callus multiplication for study of steviol glycosides in callus
culture.
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: Particle boards were prepared from Maize cob (MC) and urea-formaldehyde resin (UFR) on compression moulding machine. The amount of MC was varied from 50-120g while 30g of UFR was kept constant. Some mechanical properties of the particle boards were tested using the standard ASM methods. The results show that as the MC content increased from 50- 120g in 30g UFR, the hardness increased from about 6.89 x 102 to7.51 x 102MPa. Impact strength decreased from 3.3x 10-2 to 0.45 x 10-2J/M2, while tensile strength initially increased from 2.63 x 102 to 3.14 x 102 MPa as the MC increased from 50 to 60g in 30g UFR, thereafter, it decreased to about 1.35 x 102MPa at 120g in 30g content.
Abstract: The production of a plant can be measured in terms of
seeds. The generation of seeds plays a critical role in our social and
daily life. The fruit production which generates seeds, depends on the
various parameters of the plant, such as shoot length, leaf number,
root length, root number, etc When the plant is growing, some leaves
may be lost and some new leaves may appear. It is very difficult to
use the number of leaves of the tree to calculate the growth of the
plant.. It is also cumbersome to measure the number of roots and
length of growth of root in several time instances continuously after
certain initial period of time, because roots grow deeper and deeper
under ground in course of time. On the contrary, the shoot length of
the tree grows in course of time which can be measured in different
time instances. So the growth of the plant can be measured using the
data of shoot length which are measured at different time instances
after plantation. The environmental parameters like temperature, rain
fall, humidity and pollution are also play some role in production of
yield. The soil, crop and distance management are taken care to
produce maximum amount of yields of plant. The data of the growth
of shoot length of some mustard plant at the initial stage (7,14,21 &
28 days after plantation) is available from the statistical survey by a
group of scientists under the supervision of Prof. Dilip De. In this
paper, initial shoot length of Ken( one type of mustard plant) has
been used as an initial data. The statistical models, the methods of
fuzzy logic and neural network have been tested on this mustard
plant and based on error analysis (calculation of average error) that
model with minimum error has been selected and can be used for the
assessment of shoot length at maturity. Finally, all these methods
have been tested with other type of mustard plants and the particular
soft computing model with the minimum error of all types has been
selected for calculating the predicted data of growth of shoot length.
The shoot length at the stage of maturity of all types of mustard
plants has been calculated using the statistical method on the
predicted data of shoot length.
Abstract: The prediction of Software quality during development life cycle of software project helps the development organization to make efficient use of available resource to produce the product of highest quality. “Whether a module is faulty or not" approach can be used to predict quality of a software module. There are numbers of software quality prediction models described in the literature based upon genetic algorithms, artificial neural network and other data mining algorithms. One of the promising aspects for quality prediction is based on clustering techniques. Most quality prediction models that are based on clustering techniques make use of K-means, Mixture-of-Guassians, Self-Organizing Map, Neural Gas and fuzzy K-means algorithm for prediction. In all these techniques a predefined structure is required that is number of neurons or clusters should be known before we start clustering process. But in case of Growing Neural Gas there is no need of predetermining the quantity of neurons and the topology of the structure to be used and it starts with a minimal neurons structure that is incremented during training until it reaches a maximum number user defined limits for clusters. Hence, in this work we have used Growing Neural Gas as underlying cluster algorithm that produces the initial set of labeled cluster from training data set and thereafter this set of clusters is used to predict the quality of test data set of software modules. The best testing results shows 80% accuracy in evaluating the quality of software modules. Hence, the proposed technique can be used by programmers in evaluating the quality of modules during software development.