Abstract: The present paper discusses the selection of process
parameters for obtaining optimal nanocrystallites size in the CuOZrO2
catalyst. There are some parameters changing the inorganic
structure which have an influence on the role of hydrolysis and
condensation reaction. A statistical design test method is
implemented in order to optimize the experimental conditions of
CuO-ZrO2 nanoparticles preparation. This method is applied for the
experiments and L16 orthogonal array standard. The crystallites size
is considered as an index. This index will be used for the analysis in
the condition where the parameters vary. The effect of pH, H2O/
precursor molar ratio (R), time and temperature of calcination,
chelating agent and alcohol volume are particularity investigated
among all other parameters. In accordance with the results of
Taguchi, it is found that temperature has the greatest impact on the
particle size. The pH and H2O/ precursor molar ratio have low
influences as compared with temperature. The alcohol volume as
well as the time has almost no effect as compared with all other
parameters. Temperature also has an influence on the morphology
and amorphous structure of zirconia. The optimal conditions are
determined by using Taguchi method. The nanocatalyst is studied by
DTA-TG, XRD, EDS, SEM and TEM. The results of this research
indicate that it is possible to vary the structure, morphology and
properties of the sol-gel by controlling the above-mentioned
parameters.
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: Kernel function, which allows the formulation of nonlinear variants of any algorithm that can be cast in terms of dot products, makes the Support Vector Machines (SVM) have been successfully applied in many fields, e.g. classification and regression. The importance of kernel has motivated many studies on its composition. It-s well-known that reproducing kernel (R.K) is a useful kernel function which possesses many properties, e.g. positive definiteness, reproducing property and composing complex R.K by simple operation. There are two popular ways to compute the R.K with explicit form. One is to construct and solve a specific differential equation with boundary value whose handicap is incapable of obtaining a unified form of R.K. The other is using a piecewise integral of the Green function associated with a differential operator L. The latter benefits the computation of a R.K with a unified explicit form and theoretical analysis, whereas there are relatively later studies and fewer practical computations. In this paper, a new algorithm for computing a R.K is presented. It can obtain the unified explicit form of R.K in general reproducing kernel Hilbert space. It avoids constructing and solving the complex differential equations manually and benefits an automatic, flexible and rigorous computation for more general RKHS. In order to validate that the R.K computed by the algorithm can be used in SVM well, some illustrative examples and a comparison between R.K and Gaussian kernel (RBF) in support vector regression are presented. The result shows that the performance of R.K is close or slightly superior to that of RBF.
Abstract: Laser Metal Deposition (LMD) is an additive manufacturing process with capabilities that include: producing new
part directly from 3 Dimensional Computer Aided Design (3D CAD)
model, building new part on the existing old component and repairing an existing high valued component parts that would have
been discarded in the past. With all these capabilities and its advantages over other additive manufacturing techniques, the
underlying physics of the LMD process is yet to be fully understood probably because of high interaction between the processing
parameters and studying many parameters at the same time makes it
further complex to understand. In this study, the effect of laser power
and powder flow rate on physical properties (deposition height and
deposition width), metallurgical property (microstructure) and
mechanical (microhardness) properties on laser deposited most
widely used aerospace alloy are studied. Also, because the Ti6Al4V
is very expensive, and LMD is capable of reducing buy-to-fly ratio
of aerospace parts, the material utilization efficiency is also studied.
Four sets of experiments were performed and repeated to establish repeatability using laser power of 1.8 kW and 3.0 kW, powder flow
rate of 2.88 g/min and 5.67 g/min, and keeping the gas flow rate and
scanning speed constant at 2 l/min and 0.005 m/s respectively. The
deposition height / width are found to increase with increase in laser
power and increase in powder flow rate. The material utilization is favoured by higher power while higher powder flow rate reduces
material utilization. The results are presented and fully discussed.
Abstract: Medical images require special safety and confidentiality because critical judgment is done on the information provided by medical images. Transmission of medical image via internet or mobile phones demands strong security and copyright protection in telemedicine applications. Here, highly secured and robust watermarking technique is proposed for transmission of image data via internet and mobile phones. The Region of Interest (ROI) and Non Region of Interest (RONI) of medical image are separated. Only RONI is used for watermark embedding. This technique results in exact recovery of watermark with standard medical database images of size 512x512, giving 'correlation factor' equals to 1. The correlation factor for different attacks like noise addition, filtering, rotation and compression ranges from 0.90 to 0.95. The PSNR with weighting factor 0.02 is up to 48.53 dBs. The presented scheme is non blind and embeds hospital logo of 64x64 size.
Abstract: Recent quasi-experimental evaluation of the Canadian Active Labour Market Policies (ALMP) by Human Resources and Skills Development Canada (HRSDC) has provided an opportunity to examine alternative methods to estimating the incremental effects of Employment Benefits and Support Measures (EBSMs) on program participants. The focus of this paper is to assess the efficiency and robustness of inverse probability weighting (IPW) relative to kernel matching (KM) in the estimation of program effects. To accomplish this objective, the authors compare pairs of 1,080 estimates, along with their associated standard errors, to assess which type of estimate is generally more efficient and robust. In the interest of practicality, the authorsalso document the computationaltime it took to produce the IPW and KM estimates, respectively.
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: R&D risk management has been suggested as one of
the management approaches for accomplishing the goals of public
R&D investment. The investment in basic science and core technology
development is the essential roles of government for securing the
social base needed for continuous economic growth. And, it is also an
important role of the science and technology policy sectors to generate
a positive environment in which the outcomes of public R&D can be
diffused in a stable fashion by controlling the uncertainties and risk
factors in advance that may arise during the application of such
achievements to society and industry. Various policies have already
been implemented to manage uncertainties and variables that may
have negative impact on accomplishing public R& investment goals.
But we may derive new policy measures for complementing the
existing policies and for exploring progress direction by analyzing
them in a policy package from the viewpoint of R&D risk
management.
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: The present paper develops and validates a numerical procedure for the calculation of turbulent combustive flow in converging and diverging ducts and throuh simulation of the heat transfer processes, the amount of production and spread of Nox pollutant has been measured. A marching integration solution procedure employing the TDMA is used to solve the discretized equations. The turbulence model is the Prandtl Mixing Length method. Modeling the combustion process is done by the use of Arrhenius and Eddy Dissipation method. Thermal mechanism has been utilized for modeling the process of forming the nitrogen oxides. Finite difference method and Genmix numerical code are used for numerical solution of equations. Our results indicate the important influence of the limiting diverging angle of diffuser on the coefficient of recovering of pressure. Moreover, due to the intense dependence of Nox pollutant to the maximum temperature in the domain with this feature, the Nox pollutant amount is also in maximum level.
Abstract: In this paper, we study the numerical method for solving second-order fuzzy differential equations using Adomian method under strongly generalized differentiability. And, we present an example with initial condition having four different solutions to illustrate the efficiency of the proposed method under strongly generalized differentiability.
Abstract: The problem of mapping tasks onto a computational grid with the aim to minimize the power consumption and the makespan subject to the constraints of deadlines and architectural requirements is considered in this paper. To solve this problem, we propose a solution from cooperative game theory based on the concept of Nash Bargaining Solution. The proposed game theoretical technique is compared against several traditional techniques. The experimental results show that when the deadline constraints are tight, the proposed technique achieves superior performance and reports competitive performance relative to the optimal solution.
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: This paper presents comparative emission study of
newly introduced gasoline/LPG bifuel automotive engine in Indian
market. Emissions were tested as per LPG-Bharat stage III driving
cycle. Emission tests were carried out for urban cycle and extra urban
cycle. Total time for urban and extra urban cycle was 1180 sec.
Engine was run in LPG mode by using conversion system. Emissions
were tested as per standard procedure and were compared. Corrected
emissions were computed by deducting ambient reading from sample
reading. Paper describes detail emission test procedure and results
obtained. CO emissions were in the range of38.9 to 111.3 ppm. HC
emissions were in the range of 18.2 to 62.6 ppm. Nox emissions were
08 to 3.9 ppm and CO2 emissions were from 6719.2 to 8051 ppm.
Paper throws light on emission results of LPG vehicles recently
introduced in Indian automobile market. Objectives of this
experimental study were to measure emissions of engines in gasoline
& LPG mode and compare them.
Abstract: Very few studies have examined performance
implications of strategic alliance announcements in the information
technologies industry from a resource-based view. Furthermore, none
of these studies have investigated resource congruence and alliance
motive as potential sources of abnormal firm performance. This paper
extends upon current resource-based literature to discover and explore
linkages between these concepts and the practical performance of
strategic alliances. This study finds that strategic alliance
announcements have provided overall abnormal positive returns, and
that marketing alliances with marketing resource incongruence have
also contributed to significant firm performance.
Abstract: The purpose of this study was primarily assessing how important economic factors namely: The Thai export price of white rice, the exchange rate, and the world rice consumption affect the overall Thai white rice export, using historical data during the period 1989-2013 from the Thai Rice Exporters Association, and Food and Agricultural Organization of the United Nations. The co-integration method, regression analysis, and error correction model were applied to investigate the econometric model. The findings indicated that in the long-run, the world rice consumption, the exchange rate, and the Thai export price of white rice were the important factors affecting the export quantity of Thai white rice respectively, as indicated by their significant coefficients. Meanwhile, the rice export price was an important factor affecting the export quantity of Thai white rice in the short-run. This information is useful in the business, export opportunities, price competitiveness, and policymaker in Thailand.
Abstract: This paper argues that a product development exercise
involves in addition to the conventional stages, several decisions
regarding other aspects. These aspects should be addressed
simultaneously in order to develop a product that responds to the
customer needs and that helps realize objectives of the stakeholders
in terms of profitability, market share and the like. We present a
framework that encompasses these different development
dimensions. The framework shows that a product development
methodology such as the Quality Function Deployment (QFD) is the
basic tool which allows definition of the target specifications of a
new product. Creativity is the first dimension that enables the
development exercise to live and end successfully. A number of
group processes need to be followed by the development team in
order to ensure enough creativity and innovation. Secondly,
packaging is considered to be an important extension of the product.
Branding strategies, quality and standardization requirements,
identification technologies, design technologies, production
technologies and costing and pricing are also integral parts to the
development exercise. These dimensions constitute the proposed
framework. The paper also presents a mathematical model used to
calculate the design targets based on the target costing principle. The
framework is used to study a case of a new product development in
the telecommunications services sector.
Abstract: Organizational structure of the Turkish state
universities is a form of bureaucracy, a high efficient system in
rational and formal control. According to the dimensional approach
bureaucracy can occur in an organization in a degree, as some
bureaucracy characteristics can be stronger than others. In addition,
the units of an organization due to their different specific
characteristic properties can perceive the bureaucracy differently. In
the study, Hall-s Organizational Inventory, which was developed for
evaluating the degree of bureaucratization from the dimensional
perspective, is used to find out if there is a difference in the
perception of the bureaucracy between the academicians working in
three different departments and two faculties in the same university.
Abstract: This paper discusses a new, systematic approach to
the synthesis of a NP-hard class of non-regenerative Boolean
networks, described by FON[FOFF]={mi}[{Mi}], where for every
mj[Mj]∈{mi}[{Mi}], there exists another mk[Mk]∈{mi}[{Mi}], such
that their Hamming distance HD(mj, mk)=HD(Mj, Mk)=O(n), (where
'n' represents the number of distinct primary inputs). The method
automatically ensures exact minimization for certain important selfdual
functions with 2n-1 points in its one-set. The elements meant for
grouping are determined from a newly proposed weighted incidence
matrix. Then the binary value corresponding to the candidate pair is
correlated with the proposed binary value matrix to enable direct
synthesis. We recommend algebraic factorization operations as a post
processing step to enable reduction in literal count. The algorithm
can be implemented in any high level language and achieves best
cost optimization for the problem dealt with, irrespective of the
number of inputs. For other cases, the method is iterated to
subsequently reduce it to a problem of O(n-1), O(n-2),.... and then
solved. In addition, it leads to optimal results for problems exhibiting
higher degree of adjacency, with a different interpretation of the
heuristic, and the results are comparable with other methods.
In terms of literal cost, at the technology independent stage, the
circuits synthesized using our algorithm enabled net savings over
AOI (AND-OR-Invert) logic, AND-EXOR logic (EXOR Sum-of-
Products or ESOP forms) and AND-OR-EXOR logic by 45.57%,
41.78% and 41.78% respectively for the various problems.
Circuit level simulations were performed for a wide variety of
case studies at 3.3V and 2.5V supply to validate the performance of
the proposed method and the quality of the resulting synthesized
circuits at two different voltage corners. Power estimation was
carried out for a 0.35micron TSMC CMOS process technology. In
comparison with AOI logic, the proposed method enabled mean
savings in power by 42.46%. With respect to AND-EXOR logic, the
proposed method yielded power savings to the tune of 31.88%, while
in comparison with AND-OR-EXOR level networks; average power
savings of 33.23% was obtained.
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.