Abstract: Due to the non- intuitive nature of Quantum
algorithms, it becomes difficult for a classically trained person to
efficiently construct new ones. So rather than designing new
algorithms manually, lately, Genetic algorithms (GA) are being
implemented for this purpose. GA is a technique to automatically
solve a problem using principles of Darwinian evolution. This has
been implemented to explore the possibility of evolving an n-qubit
circuit when the circuit matrix has been provided using a set of
single, two and three qubit gates. Using a variable length population
and universal stochastic selection procedure, a number of possible
solution circuits, with different number of gates can be obtained for
the same input matrix during different runs of GA. The given
algorithm has also been successfully implemented to obtain two and
three qubit Boolean circuits using Quantum gates. The results
demonstrate the effectiveness of the GA procedure even when the
search spaces are large.
Abstract: This paper proposes view-point insensitive human
pose recognition system using neural network. Recognition system
consists of silhouette image capturing module, data driven database,
and neural network. The advantages of our system are first, it is
possible to capture multiple view-point silhouette images of 3D human
model automatically. This automatic capture module is helpful to
reduce time consuming task of database construction. Second, we
develop huge feature database to offer view-point insensitivity at pose
recognition. Third, we use neural network to recognize human pose
from multiple-view because every pose from each model have similar
feature patterns, even though each model has different appearance and
view-point. To construct database, we need to create 3D human model
using 3D manipulate tools. Contour shape is used to convert silhouette
image to feature vector of 12 degree. This extraction task is processed
semi-automatically, which benefits in that capturing images and
converting to silhouette images from the real capturing environment is
needless. We demonstrate the effectiveness of our approach with
experiments on virtual environment.
Abstract: In this study, we used a two-stage process and
potassium hydroxide (KOH) to transform waste biomass (rice straw)
into activated carbon and then evaluated the adsorption capacity of the
waste for removing carbofuran from an aqueous solution. Activated
carbon was fast and effective for the removal of carbofuran because of
its high surface area. The native and carbofuran-loaded adsorbents
were characterized by elemental analysis. Different adsorption
parameters, such as the initial carbofuran concentration, contact time,
temperature and pH for carbofuran adsorption, were studied using a
batch system. This study demonstrates that rice straw can be very
effective in the adsorption of carbofuran from bodies of water.
Abstract: The classic problem of recovering arbitrary values of
a band-limited signal from its samples has an added complication
in software radio applications; namely, the resampling calculations
inevitably fold aliases of the analog signal back into the original
bandwidth. The phenomenon is quantified by the spur-free dynamic
range. We demonstrate how a novel application of the Remez (Parks-
McClellan) algorithm permits optimal signal recovery and SFDR, far
surpassing state-of-the-art resamplers.
Abstract: The Beijing road traffic system, as a typical huge
urban traffic system, provides a platform for analyzing the complex
characteristics and the evolving mechanisms of urban traffic systems.
Based on dynamic network theory, we construct the dynamic model
of the Beijing road traffic system in which the dynamical properties
are described completely. Furthermore, we come into the conclusion
that urban traffic systems can be viewed as static networks, stochastic
networks and complex networks at different system phases by
analyzing the structural randomness. As well as, we demonstrate the
evolving process of the Beijing road traffic network based on real
traffic data, validate the stochastic characteristics and the scale-free
property of the network at different phases
Abstract: Sustainability in rural production system can only be achieved if it can suitably satisfy the local requirement as well as the outside demand with the changing time. With the increased pressure from the food sector in a globalised world, the agrarian economy
needs to re-organise its cultivable land system to be compatible with new management practices as well as the multiple needs of various stakeholders and the changing resource scenario. An attempt has been made to transform this problem into a multi-objective decisionmaking problem considering various objectives, resource constraints and conditional constraints. An interactive fuzzy multi-objective
programming approach has been used for such a purpose taking a
case study in Indian context to demonstrate the validity of the method.
Abstract: This study analyzed the creativity of student teams
participating in an exploratory information system development
project (ISDP) and examined antecedents of their creativity. By using
partial least squares (PLS) to analyze a sample of thirty-six teams
enrolled in an information system department project training course
that required three semesters of project-based lessons, the results
found social capitals (structural, relational and cognitive social capital)
positively influence knowledge integration. However, relational social
capital does not significantly influence knowledge integration.
Knowledge integration positively affects team creativity. This study
also demonstrated that social capitals significantly influence team
creativity through knowledge integration. The implications of our
findings for future research are discussed.
Abstract: Remarkable changes, like the progress in the ability to understand others' minds, can be identified in several socio-cognitive dimensions between age four and seven. Recently, the parenting attitudes have been considerate as one of the potential extrinsic modifiers of these important developmental aspects. The aim of present study is to explore the relationship among authoritarian parenting attitudes and individual differences in Theory of Mind performance. The study included ninety-two Costarrican preschoolers. Six False-belief tasks, an Advanced Theory of Mind test and the Parenting Attitudes Inventory were used. The results demonstrate that participants with high and low Authoritarian Parenting Received differ in their performance on First and Second Order False-belief tasks, but not in Advanced Theory of Mind tasks. Theoretical considerations about possible explanations regarding these results are discussed and methodological limitations are considered to shed light over future directions.
Abstract: Among all geo-hydrological relationships, rainfallrunoff
relationship is of utmost importance in any hydrological
investigation and water resource planning. Spatial variation, lag time
involved in obtaining areal estimates for the basin as a whole can
affect the parameterization in design stage as well as in planning
stage. In conventional hydrological processing of data, spatial aspect
is either ignored or interpolated at sub-basin level. Temporal
variation when analysed for different stages can provide clues for its
spatial effectiveness. The interplay of space-time variation at pixel
level can provide better understanding of basin parameters.
Sustenance of design structures for different return periods and their
spatial auto-correlations should be studied at different geographical
scales for better management and planning of water resources.
In order to understand the relative effect of spatio-temporal
variation in hydrological data network, a detailed geo-hydrological
analysis of Betwa river catchment falling in Lower Yamuna Basin is
presented in this paper. Moreover, the exact estimates about the
availability of water in the Betwa river catchment, especially in the
wake of recent Betwa-Ken linkage project, need thorough scientific
investigation for better planning. Therefore, an attempt in this
direction is made here to analyse the existing hydrological and
meteorological data with the help of SPSS, GIS and MS-EXCEL
software. A comparison of spatial and temporal correlations at subcatchment
level in case of upper Betwa reaches has been made to
demonstrate the representativeness of rain gauges. First, flows at
different locations are used to derive correlation and regression
coefficients. Then, long-term normal water yield estimates based on
pixel-wise regression coefficients of rainfall-runoff relationship have
been mapped. The areal values obtained from these maps can
definitely improve upon estimates based on point-based
extrapolations or areal interpolations.
Abstract: The higher compounded growth rates coupled with
favourable demographics in emerging markets portend abundant
opportunities for multinational organizations. With many
organizations competing for talent in these growing markets, their
ability to succeed will depend on their understanding of local
workforce needs and aspirations. Using data from the Towers Watson
2010 Global Workforce Study, this paper highlights differences in
employee engagement, turnover risks, and attraction and retention
drivers between the two markets. Apart from looking at the
traditional drivers of employee engagement, the study also explores
the value placed by employees on elements like a strong senior
leadership, managerial capabilities and career advancement
opportunities. Results reveal that emerging markets employees seem
to be more engaged and value the non-traditional elements more
highly than the developed markets employees.
Abstract: Ants are fascinating creatures that demonstrate the
ability to find food and bring it back to their nest. Their ability as a
colony, to find paths to food sources has inspired the development of
algorithms known as Ant Colony Systems (ACS). The principle of
cooperation forms the backbone of such algorithms, commonly used
to find solutions to problems such as the Traveling Salesman
Problem (TSP). Ants communicate to each other through chemical
substances called pheromones. Modeling individual ants- ability to
manipulate this substance can help an ACS find the best solution.
This paper introduces a Dynamic Ant Colony System with threelevel
updates (DACS3) that enhance an existing ACS. Experiments
were conducted to observe single ant behavior in a colony of
Malaysian House Red Ants. Such behavior was incorporated into the
DACS3 algorithm. We benchmark the performance of DACS3 versus
DACS on TSP instances ranging from 14 to 100 cities. The result
shows that the DACS3 algorithm can achieve shorter distance in
most cases and also performs considerably faster than DACS.
Abstract: For a generalized Hermite sinosiodal / hyperbolic Gaussian beam passing through an ABCD system with a finite aperture, the propagation properties are derived using the Collins integral. The results are obtained in the form of intensity graphs indicating that previously demonstrated rules of reciprocity are applicable, while the existence of the aperture accelerates this transformation.
Abstract: Self-organizing map (SOM) is a well known data
reduction technique used in data mining. It can reveal structure in
data sets through data visualization that is otherwise hard to detect
from raw data alone. However, interpretation through visual
inspection is prone to errors and can be very tedious. There are
several techniques for the automatic detection of clusters of code
vectors found by SOM, but they generally do not take into account
the distribution of code vectors; this may lead to unsatisfactory
clustering and poor definition of cluster boundaries, particularly
where the density of data points is low. In this paper, we propose the
use of an adaptive heuristic particle swarm optimization (PSO)
algorithm for finding cluster boundaries directly from the code
vectors obtained from SOM. The application of our method to
several standard data sets demonstrates its feasibility. PSO algorithm
utilizes a so-called U-matrix of SOM to determine cluster boundaries;
the results of this novel automatic method compare very favorably to
boundary detection through traditional algorithms namely k-means
and hierarchical based approach which are normally used to interpret
the output of SOM.
Abstract: Nowadays, the demand for high product quality
focuses extensive attention to the quality of machined surface. The
(CNC) milling machine facilities provides a wide variety of
parameters set-up, making the machining process on the glass
excellent in manufacturing complicated special products compared to
other machining processes. However, the application of grinding
process on the CNC milling machine could be an ideal solution to
improve the product quality, but adopting the right machining
parameters is required. In glass milling operation, several machining
parameters are considered to be significant in affecting surface
roughness. These parameters include the lubrication pressure, spindle
speed, feed rate and depth of cut. In this research work, a fuzzy logic
model is offered to predict the surface roughness of a machined
surface in glass milling operation using CBN grinding tool. Four
membership functions are allocated to be connected with each input
of the model. The predicted results achieved via fuzzy logic model
are compared to the experimental result. The result demonstrated
settlement between the fuzzy model and experimental results with the
93.103% accuracy.
Abstract: Text Mining is around applying knowledge discovery techniques to unstructured text is termed knowledge discovery in text (KDT), or Text data mining or Text Mining. In Neural Network that address classification problems, training set, testing set, learning rate are considered as key tasks. That is collection of input/output patterns that are used to train the network and used to assess the network performance, set the rate of adjustments. This paper describes a proposed back propagation neural net classifier that performs cross validation for original Neural Network. In order to reduce the optimization of classification accuracy, training time. The feasibility the benefits of the proposed approach are demonstrated by means of five data sets like contact-lenses, cpu, weather symbolic, Weather, labor-nega-data. It is shown that , compared to exiting neural network, the training time is reduced by more than 10 times faster when the dataset is larger than CPU or the network has many hidden units while accuracy ('percent correct') was the same for all datasets but contact-lences, which is the only one with missing attributes. For contact-lences the accuracy with Proposed Neural Network was in average around 0.3 % less than with the original Neural Network. This algorithm is independent of specify data sets so that many ideas and solutions can be transferred to other classifier paradigms.
Abstract: Recently, it is found that telegraph equation is more suitable than ordinary diffusion equation in modelling reaction diffusion for such branches of sciences. In this paper, a numerical solution for the one-dimensional hyperbolic telegraph equation by using the collocation method using the septic splines is proposed. The scheme works in a similar fashion as finite difference methods. Test problems are used to validate our scheme by calculate L2-norm and L∞-norm. The accuracy of the presented method is demonstrated by two test problems. The numerical results are found to be in good agreement with the exact solutions.
Abstract: Food mileage is one of the important issues concerning environmental sustainability. In this research we have utilized a prototype platform with iterative user-centered testing. With these findings we successfully demonstrate the use of the context of persuasive methods to influence users- attitudes towards the sustainable concept.
Abstract: In the present research, a finite element model is
presented to study the geometrical and material nonlinear behavior of
reinforced concrete plane frames considering soil-structure
interaction. The nonlinear behaviors of concrete and reinforcing steel
are considered both in compression and tension up to failure. The
model takes account also for the number, diameter, and distribution
of rebar along every cross section. Soil behavior is taken into
consideration using four different models; namely: linear-, nonlinear
Winkler's model, and linear-, nonlinear continuum model. A
computer program (NARC) is specially developed in order to
perform the analysis. The results achieved by the present model show
good agreement with both theoretical and experimental published
literature. The nonlinear behavior of a rectangular frame resting on
soft soil up to failure using the proposed model is introduced for
demonstration.
Abstract: From past many decades human beings are suffering
from plethora of natural disasters. Occurrence of disasters is a
frequent process; it changes conceptual myths as more and more
advancement are made. Although we are living in technological era
but in developing countries like Pakistan disasters are shaped by
socially constructed roles. The need is to understand the most
vulnerable group of society i.e. females; their issues are complex in
nature because of undermined gender status in the society. There is a
need to identify maximum issues regarding females and to enhance
the achievement of millennium development goals (MDGs). Gender
issues are of great concern all around the globe including Pakistan.
Here female visibility in society is low, and also during disasters, the
failure to understand the reality that concentrates on double burden
including productive and reproductive care. Women have to
contribute a lot in society so we need to make them more disaster
resilient. For this non-structural measures like awareness, trainings
and education must be carried out. In rural and in urban settings in
any disaster like earthquake or flood, elements like gender
perspective, their age, physical health, demographic issues contribute
towards vulnerability. In Pakistan the gender issues in disasters were
of less concern before 2005 earthquake and 2010 floods. Significant
achievements are made after 2010 floods when gender and child cell
was created to provide all facilities to women and girls. The aim of
the study is to highlight all necessary facilities in a disaster to build
coping mechanism in females from basic rights till advance level
including education.
Abstract: Several methods have been proposed for color image
compression but the reconstructed image had very low signal to noise
ratio which made it inefficient. This paper describes a lossy
compression technique for color images which overcomes the
drawbacks. The technique works on spatial domain where the pixel
values of RGB planes of the input color image is mapped onto two
dimensional planes. The proposed technique produced better results
than JPEG2000, 2DPCA and a comparative study is reported based
on the image quality measures such as PSNR and MSE.Experiments
on real time images are shown that compare this methodology with
previous ones and demonstrate its advantages.