Abstract: Rapid urbanization, industrialization and population
growth have led to an increase in number of automobiles that cause
air pollution. It is estimated that road traffic contributes 60% of air
pollution in urban areas. A case by case assessment is required to
predict the air quality in urban situations, so as to evolve certain
traffic management measures to maintain the air quality levels with
in the tolerable limits. Calicut city in the state of Kerala, India has
been chosen as the study area. Carbon Monoxide (CO) concentration
was monitored at 15 links in Calicut city and air quality performance
was evaluated over each link. The CO pollutant concentration values
were compared with the National Ambient Air Quality Standards
(NAAQS), and the CO values were predicted by using CALINE4 and
IITLS and Linear regression models. The study has revealed that
linear regression model performs better than the CALINE4 and
IITLS models. The possible association between CO pollutant
concentration and traffic parameters like traffic flow, type of vehicle,
and traffic stream speed was also evaluated.
Abstract: The performance and the plasma created by a pulsed
magnetoplasmadynamic thruster for small satellite application is
studied to understand better the ablation and plasma propagation
processes occurring during the short-time discharge. The results can
be applied to improve the quality of the thruster in terms of efficiency,
and to tune the propulsion system to the needs required by the satellite
mission. Therefore, plasma measurements with a high-speed camera
and induction probes, and performance measurements of mass bit
and impulse bit were conducted. Values for current sheet propagation
speed, mean exhaust velocity and thrust efficiency were derived from
these experimental data. A maximum in current sheet propagation
was found by the high-speed camera measurements for a medium
energy input and confirmed by the induction probes. A quasilinear
tendency between the mass bit and the energy input, the current
action integral respectively, was found, as well as a linear tendency
between the created impulse and the discharge energy. The highest
mean exhaust velocity and thrust efficiency was found for the highest
energy input.
Abstract: For more than 120 years, gold mining formed the
backbone the South Africa-s economy. The consequence of mine
closure was observed in large-scale land degradation and widespread
pollution of surface water and groundwater. This paper investigates
the feasibility of using natural zeolite in removing heavy metals
contaminating the Wonderfonteinspruit Catchment Area (WCA), a
water stream with high levels of heavy metals and radionuclide
pollution. Batch experiments were conducted to study the adsorption
behavior of natural zeolite with respect to Fe2+, Mn2+, Ni2+, and Zn2+.
The data was analysed using the Langmuir and Freudlich isotherms.
Langmuir was found to correlate the adsorption of Fe2+, Mn2+, Ni2+,
and Zn2+ better, with the adsorption capacity of 11.9 mg/g, 1.2 mg/g,
1.3 mg/g, and 14.7 mg/g, respectively. Two kinetic models namely,
pseudo-first order and pseudo second order were also tested to fit the
data. Pseudo-second order equation was found to be the best fit for
the adsorption of heavy metals by natural zeolite. Zeolite
functionalization with humic acid increased its uptake ability.
Abstract: As the gradual increase of the enterprise scale, the
firms may possess many manufacturing plants located in different
places geographically. This change will result in the multi-site
production planning problems under the environment of multiple
plants or production resources. Our research proposes the structural
framework to analyze the multi-site planning problems. The analytical
framework is composed of six elements: multi-site conceptual model,
product structure (bill of manufacturing), production strategy,
manufacturing capability and characteristics, production planning
constraints, and key performance indicators. As well as the discussion
of these six ingredients, we also review related literatures in this paper
to match our analytical framework. Finally we take a real-world
practical example of a TFT-LCD manufacturer in Taiwan to explain
our proposed analytical framework for the multi-site production
planning problems.
Abstract: In this paper a stochastic scenario-based model predictive control applied to molten salt storage systems in concentrated solar tower power plant is presented. The main goal of this study is to build up a tool to analyze current and expected future resources for evaluating the weekly power to be advertised on electricity secondary market. This tool will allow plant operator to maximize profits while hedging the impact on the system of stochastic variables such as resources or sunlight shortage.
Solving the problem first requires a mixed logic dynamic modeling of the plant. The two stochastic variables, respectively the sunlight incoming energy and electricity demands from secondary market, are modeled by least square regression. Robustness is achieved by drawing a certain number of random variables realizations and applying the most restrictive one to the system. This scenario approach control technique provides the plant operator a confidence interval containing a given percentage of possible stochastic variable realizations in such a way that robust control is always achieved within its bounds. The results obtained from many trajectory simulations show the existence of a ‘’reliable’’ interval, which experimentally confirms the algorithm robustness.
Abstract: In this paper, we consider the problem of logic simplification for a special class of logic functions, namely complementary Boolean functions (CBF), targeting low power implementation using static CMOS logic style. The functions are uniquely characterized by the presence of terms, where for a canonical binary 2-tuple, D(mj) ∪ D(mk) = { } and therefore, we have | D(mj) ∪ D(mk) | = 0 [19]. Similarly, D(Mj) ∪ D(Mk) = { } and hence | D(Mj) ∪ D(Mk) | = 0. Here, 'mk' and 'Mk' represent a minterm and maxterm respectively. We compare the circuits minimized with our proposed method with those corresponding to factored Reed-Muller (f-RM) form, factored Pseudo Kronecker Reed-Muller (f-PKRM) form, and factored Generalized Reed-Muller (f-GRM) form. We have opted for algebraic factorization of the Reed-Muller (RM) form and its different variants, using the factorization rules of [1], as it is simple and requires much less CPU execution time compared to Boolean factorization operations. This technique has enabled us to greatly reduce the literal count as well as the gate count needed for such RM realizations, which are generally prone to consuming more cells and subsequently more power consumption. However, this leads to a drawback in terms of the design-for-test attribute associated with the various RM forms. Though we still preserve the definition of those forms viz. realizing such functionality with only select types of logic gates (AND gate and XOR gate), the structural integrity of the logic levels is not preserved. This would consequently alter the testability properties of such circuits i.e. it may increase/decrease/maintain the same number of test input vectors needed for their exhaustive testability, subsequently affecting their generalized test vector computation. We do not consider the issue of design-for-testability here, but, instead focus on the power consumption of the final logic implementation, after realization with a conventional CMOS process technology (0.35 micron TSMC process). The quality of the resulting circuits evaluated on the basis of an established cost metric viz., power consumption, demonstrate average savings by 26.79% for the samples considered in this work, besides reduction in number of gates and input literals by 39.66% and 12.98% respectively, in comparison with other factored RM forms.
Abstract: Selection of the best possible set of suppliers has a
significant impact on the overall profitability and success of any
business. For this reason, it is usually necessary to optimize all
business processes and to make use of cost-effective alternatives for
additional savings. This paper proposes a new efficient context-aware
supplier selection model that takes into account possible changes of
the environment while significantly reducing selection costs. The
proposed model is based on data clustering techniques while
inspiring certain principles of online algorithms for an optimally
selection of suppliers. Unlike common selection models which re-run
the selection algorithm from the scratch-line for any decision-making
sub-period on the whole environment, our model considers the
changes only and superimposes it to the previously defined best set
of suppliers to obtain a new best set of suppliers. Therefore, any recomputation
of unchanged elements of the environment is avoided
and selection costs are consequently reduced significantly. A
numerical evaluation confirms applicability of this model and proves
that it is a more optimal solution compared with common static
selection models in this field.
Abstract: Predicting short term wind speed is essential in order
to prevent systems in-action from the effects of strong winds. It also
helps in using wind energy as an alternative source of energy, mainly
for Electrical power generation. Wind speed prediction has
applications in Military and civilian fields for air traffic control,
rocket launch, ship navigation etc. The wind speed in near future
depends on the values of other meteorological variables, such as
atmospheric pressure, moisture content, humidity, rainfall etc. The
values of these parameters are obtained from a nearest weather
station and are used to train various forms of neural networks. The
trained model of neural networks is validated using a similar set of
data. The model is then used to predict the wind speed, using the
same meteorological information. This paper reports an Artificial
Neural Network model for short term wind speed prediction, which
uses back propagation algorithm.
Abstract: Wireless Sensor Networks (WSNs) are wireless
networks consisting of number of tiny, low cost and low power
sensor nodes to monitor various physical phenomena like
temperature, pressure, vibration, landslide detection, presence of any
object, etc. The major limitation in these networks is the use of nonrechargeable
battery having limited power supply. The main cause of
energy consumption WSN is communication subsystem. This paper
presents an efficient grid formation/clustering strategy known as Grid
based level Clustering and Aggregation of Data (GCAD). The
proposed clustering strategy is simple and scalable that uses low duty
cycle approach to keep non-CH nodes into sleep mode thus reducing
energy consumption. Simulation results demonstrate that our
proposed GCAD protocol performs better in various performance
metrics.
Abstract: Particle Swarm Optimization (PSO) with elite PSO
parameters has been developed for power flow analysis under
practical constrained situations. Multiple solutions of the power flow
problem are useful in voltage stability assessment of power system.
A method of determination of multiple power flow solutions is
presented using a hybrid of Particle Swarm Optimization (PSO) and
local search technique. The unique and innovative learning factors of
the PSO algorithm are formulated depending upon the node power
mismatch values to be highly adaptive with the power flow problems.
The local search is applied on the pbest solution obtained by the PSO
algorithm in each iteration. The proposed algorithm performs reliably
and provides multiple solutions when applied on standard and illconditioned
systems. The test results show that the performances of
the proposed algorithm under critical conditions are better than the
conventional methods.
Abstract: Inverse kinematics analysis plays an important role in developing a robot manipulator. But it is not too easy to derive the inverse kinematic equation of a robot manipulator especially robot manipulator which has numerous degree of freedom. This paper describes an application of Artificial Neural Network for modeling the inverse kinematics equation of a robot manipulator. In this case, the robot has three degree of freedoms and the robot was implemented for drilling a printed circuit board. The artificial neural network architecture used for modeling is a multilayer perceptron networks with steepest descent backpropagation training algorithm. The designed artificial neural network has 2 inputs, 2 outputs and varies in number of hidden layer. Experiments were done in variation of number of hidden layer and learning rate. Experimental results show that the best architecture of artificial neural network used for modeling inverse kinematics of is multilayer perceptron with 1 hidden layer and 38 neurons per hidden layer. This network resulted a RMSE value of 0.01474.
Abstract: In India, the quarrel between the budding human
populace and the planet-s unchanging supply of freshwater and
falling water tables has strained attention the reuse of gray water as
an alternative water resource in rural development. This paper
present the finest design of laboratory scale gray water treatment
plant, which is a combination of natural and physical operations such
as primary settling with cascaded water flow, aeration, agitation and
filtration, hence called as hybrid treatment process. The economical
performance of the plant for treatment of bathrooms, basins and
laundries gray water showed in terms of deduction competency of
water pollutants such as COD (83%), TDS (70%), TSS (83%), total
hardness (50%), oil and grease (97%), anions (46%) and cations
(49%). Hence, this technology could be a good alternative to treat
gray water in residential rural area.
Abstract: e-Government structures permits the government to operate in a more transparent and accountable manner of which it increases the power of the individual in relation to that of the government. This paper identifies the factors that determine customer-s attitude towards e-Government services using a theoretical model based on the Technology Acceptance Model. Data relating to the constructs were collected from 200 respondents. The research model was tested using Structural Equation Modeling (SEM) techniques via the Analysis of Moment Structure (AMOS 16) computer software. SEM is a comprehensive approach to testing hypotheses about relations among observed and latent variables. The proposed model fits the data well. The results demonstrated that e- Government services acceptance can be explained in terms of compatibility and attitude towards e-Government services. The setup of the e-Government services will be compatible with the way users work and are more likely to adopt e-Government services owing to their familiarity with the Internet for various official, personal, and recreational uses. In addition, managerial implications for government policy makers, government agencies, and system developers are also discussed.
Abstract: This paper demonstrates the application of craziness based particle swarm optimization (CRPSO) technique for designing the 8th order low pass Infinite Impulse Response (IIR) filter. CRPSO, the much improved version of PSO, is a population based global heuristic search algorithm which finds near optimal solution in terms of a set of filter coefficients. Effectiveness of this algorithm is justified with a comparative study of some well established algorithms, namely, real coded genetic algorithm (RGA) and particle swarm optimization (PSO). Simulation results affirm that the proposed algorithm CRPSO, outperforms over its counterparts not only in terms of quality output i.e. sharpness at cut-off, pass band ripple, stop band ripple, and stop band attenuation but also in convergence speed with assured stability.
Abstract: This paper presents a technical speaker adaptation
method called WMLLR, which is based on maximum likelihood linear
regression (MLLR). In MLLR, a linear regression-based transform
which adapted the HMM mean vectors was calculated to maximize the
likelihood of adaptation data. In this paper, the prior knowledge of the
initial model is adequately incorporated into the adaptation. A series of
speaker adaptation experiments are carried out at a 30 famous city
names database to investigate the efficiency of the proposed method.
Experimental results show that the WMLLR method outperforms the
conventional MLLR method, especially when only few utterances
from a new speaker are available for adaptation.
Abstract: In this paper, Tobephobia (TBP) alludes to the fear of
failure experienced by teachers to manage curriculum change. TBP is
an emerging concept and it extends the boundaries of research in
terms of how we view achievement and failure in education.
Outcomes-based education (OBE) was introduced fifteen years ago
in South African schools without simultaneously upgrading teachers-
professional competencies. This exploratory research, therefore
examines a simple question: What is the impact of TBP and OBE on
teachers? Teacher ineptitude to cope with the OBE curriculum in the
classroom is a serious problem affecting large numbers of South
African teachers. This exploratory study sought to determine the
perceived negative impact of OBE and TBP on teachers. A survey
was conducted amongst 311 teachers in Port Elizabeth and Durban,
South Africa. The results confirm the very negative impact of TBP
and OBE on teachers. This exploratory study authenticates the
existence of TBP.
Abstract: The number of framework conceived for e-learning
constantly increase, unfortunately the creators of learning materials
and educational institutions engaged in e-formation adopt a
“proprietor" approach, where the developed products (courses,
activities, exercises, etc.) can be exploited only in the framework
where they were conceived, their uses in the other learning
environments requires a greedy adaptation in terms of time and
effort. Each one proposes courses whose organization, contents,
modes of interaction and presentations are unique for all learners,
unfortunately the latter are heterogeneous and are not interested by
the same information, but only by services or documents adapted to
their needs. Currently the new tendency for the framework
conceived for e-learning, is the interoperability of learning materials,
several standards exist (DCMI (Dublin Core Metadata Initiative)[2],
LOM (Learning Objects Meta data)[1], SCORM (Shareable Content
Object Reference Model)[6][7][8], ARIADNE (Alliance of Remote
Instructional Authoring and Distribution Networks for Europe)[9],
CANCORE (Canadian Core Learning Resource Metadata
Application Profiles)[3]), they converge all to the idea of learning
objects. They are also interested in the adaptation of the learning
materials according to the learners- profile. This article proposes an
approach for the composition of courses adapted to the various
profiles (knowledge, preferences, objectives) of learners, based on
two ontologies (domain to teach and educational) and the learning
objects.
Abstract: The effects of down slope steepness on soil splash distribution under a water drop impact have been investigated in this study. The equipment used are the burette to simulate a water drop, a splash cup filled with sandy soil which forms the source area and a splash board to collect the ejected particles. The results found in this study have shown that the apparent mass increased with increasing downslope angle following a linear regression equation with high coefficient of determination. In the same way, the radial soil splash distribution over the distance has been analyzed statistically, and an exponential function was the best fit of the relationship for the different slope angles. The curves and the regressions equations validate the well known FSDF and extend the theory of Van Dijk.
Abstract: Deep and radical social reforms of the last century-s
nineties in many Eastern European countries caused changes in
Information Technology-s (IT) field. Inefficient information
technologies were rapidly replaced with forefront IT solutions, e.g.,
in Eastern European countries there is a high level penetration of
qualitative high-speed Internet. The authors have taken part in the
introduction of those changes in Latvia-s leading IT research
institute. Grounding on their experience authors in this paper offer an
IT services based model for analysis the mentioned changes- and
development processes in the higher education and research fields,
i.e., for research e-infrastructure-s development. Compare to the
international practice such services were developed in Eastern Europe
in an untraditional way, which provided swift and positive
technological changes.
Abstract: This article outlines conceptualization and
implementation of an intelligent system capable of extracting
knowledge from databases. Use of hybridized features of both the
Rough and Fuzzy Set theory render the developed system flexibility
in dealing with discreet as well as continuous datasets. A raw data set
provided to the system, is initially transformed in a computer legible
format followed by pruning of the data set. The refined data set is
then processed through various Rough Set operators which enable
discovery of parameter relationships and interdependencies. The
discovered knowledge is automatically transformed into a rule base
expressed in Fuzzy terms. Two exemplary cancer repository datasets
(for Breast and Lung Cancer) have been used to test and implement
the proposed framework.