Abstract: Cooktop burners are widely used nowadays. In
cooktop burner design, nozzle efficiency and greenhouse
gas(GHG) emissions mainly depend on heat transfer from the
premixed flame to the impinging surface. This is a complicated
issue depending on the individual and combined effects of various
input combustion variables. Optimal operating conditions for
sustainable burner design were rarely addressed, especially in the
case of multiple slot-jet burners. Through evaluating the optimal
combination of combustion conditions for a premixed slot-jet
array, this paper develops a practical approach for the sustainable
design of gas cooktop burners. Efficiency, CO and NOx emissions
in respect of an array of slot jets using premixed flames were
analysed. Response surface experimental design were applied to
three controllable factors of the combustion process, viz.
Reynolds number, equivalence ratio and jet-to-vessel distance.
Desirability Function Approach(DFA) is the analytic technique
used for the simultaneous optimization of the efficiency and
emission responses.
Abstract: Many IT projects come to failure because of having
technical approach, focusing on the final product and lack of proper
attention to strategic alignment. Project management models quite
often have technical management view [4], [8], [13], [14]. These
models focus greatly on the finalization of the project product and the
delivery of the product to the customer. However, many project
problems are due to lack of attention to the needs and capabilities of
the organizations or disregarding how to deploy and use the product
in the organization. In this regard, in the current research we are
trying to present a solution with the purpose of raising the value of
the project in an organization. This way, the project outputs will be
properly deployed in the organization. Therefore, a comprehensive
model is presented which takes into account the whole processes
from initial step of project definition to the deployment of the final
outputs in the organization and then the definition of all roles and
responsibilities to put the model into practice. Taking into account
the opinions of experts and project managers, to prove the
performance of the model, the project problems were recognized and
based on the model, categorized and analyzed. And at the end it is
made clear that ignoring the proper definition of the project and not
having a proper understanding of the expected value on the one hand
and not supervising the emerged value in the process of production
and installment are among the most important factors that bring a
project to failure.
Abstract: This paper describes the shape optimization of impeller
blades for a anti-heeling bidirectional axial flow pump used in ships.
In general, a bidirectional axial pump has an efficiency much lower
than the classical unidirectional pump because of the symmetry of the
blade type. In this paper, by focusing on a pump impeller, the shape of
blades is redesigned to reach a higher efficiency in a bidirectional axial
pump. The commercial code employed in this simulation is CFX v.13.
CFD result of pump torque, head, and hydraulic efficiency was
compared. The orthogonal array (OA) and analysis of variance
(ANOVA) techniques and surrogate model based optimization using
orthogonal polynomial, are employed to determine the main effects
and their optimal design variables. According to the optimal design,
we confirm an effective design variable in impeller blades and explain
the optimal solution, the usefulness for satisfying the constraints of
pump torque and head.
Abstract: The multiple traveling salesman problem (mTSP) can be used to model many practical problems. The mTSP is more complicated than the traveling salesman problem (TSP) because it requires determining which cities to assign to each salesman, as well as the optimal ordering of the cities within each salesman's tour. Previous studies proposed that Genetic Algorithm (GA), Integer Programming (IP) and several neural network (NN) approaches could be used to solve mTSP. This paper compared the results for mTSP, solved with Genetic Algorithm (GA) and Nearest Neighbor Algorithm (NNA). The number of cities is clustered into a few groups using k-means clustering technique. The number of groups depends on the number of salesman. Then, each group is solved with NNA and GA as an independent TSP. It is found that k-means clustering and NNA are superior to GA in terms of performance (evaluated by fitness function) and computing time.
Abstract: Chemical detection is still a continuous challenge when
it comes to designing single-walled carbon nanotube (SWCNT)
sensors with high selectivity, especially in complex chemical
environments. A perfect example of such an environment would be in
thermally oxidized soybean oil. At elevated temperatures, oil oxidizes
through a series of chemical reactions which results in the formation of
monoacylglycerols, diacylglycerols, oxidized triacylglycerols, dimers,
trimers, polymers, free fatty acids, ketones, aldehydes, alcohols,
esters, and other minor products. In order to detect the rancidity of
oxidized soybean oil, carbon nanotube chemiresistor sensors have
been coated with polyethylenimine (PEI) to enhance the sensitivity
and selectivity. PEI functionalized SWCNTs are known to have a high
selectivity towards strong electron withdrawing molecules. The
sensors were very responsive to different oil oxidation levels and
furthermore, displayed a rapid recovery in ambient air without the
need of heating or UV exposure.
Abstract: In this paper, we propose the Modified Synchronous Detection (MSD) Method for determining the reference compensating currents of the shunt active power filter under non sinusoidal voltages conditions. For controlling the inverter switching we used the PI regulator. The numerical simulation results, using Power System Blockset Toolbox PSB of Matlab, from a complete structure, are presented and discussed.
Abstract: This paper presents an optimization technique to economic load dispatch (ELD) problems with considering the daily load patterns and generator constraints using a particle swarm optimization (PSO). The objective is to minimize the fuel cost. The optimization problem is subject to system constraints consisting of power balance and generation output of each units. The application of a constriction factor into PSO is a useful strategy to ensure convergence of the particle swarm algorithm. The proposed method is able to determine, the output power generation for all of the power generation units, so that the total constraint cost function is minimized. The performance of the developed methodology is demonstrated by case studies in test system of fifteen-generation units. The results show that the proposed algorithm scan give the minimum total cost of generation while satisfying all the constraints and benefiting greatly from saving in power loss reduction
Abstract: This paper proposed a nonlinear model predictive
control (MPC) method for the control of gantry crane. One of the main
motivations to apply MPC to control gantry crane is based on its
ability to handle control constraints for multivariable systems. A
pre-compensator is constructed to compensate the input nonlinearity
(nonsymmetric dead zone with saturation) by using its inverse
function. By well tuning the weighting function matrices, the control
system can properly compromise the control between crane position
and swing angle. The proposed control algorithm was implemented for
the control of gantry crane system in System Control Lab of University
of Technology, Sydney (UTS), and achieved desired experimental
results.
Abstract: In this study, an OCR system for segmentation,
feature extraction and recognition of Ottoman Scripts has been
developed using handwritten characters. Detection of handwritten
characters written by humans is a difficult process. Segmentation and
feature extraction stages are based on geometrical feature analysis,
followed by the chain code transformation of the main strokes of
each character. The output of segmentation is well-defined segments
that can be fed into any classification approach. The classes of main
strokes are identified through left-right Hidden Markov Model
(HMM).
Abstract: Science and technology of ultrasonic is widely used in
recent years for industrial and medicinal application. The acoustical
properties of 2-mercapto substituted pyrimidines viz.,2- Mercapto-4-
(2’,4’ –dichloro phenyl) – 6-(2’ – hydroxyl -4’ –methyl-5’ –
chlorophenyl) pyrimidine and 2 –Mercapto – 4-(4’ –chloro phenyl) –
6-(2’ – hydroxyl -4’ –methyl-5’ –chlorophenyl) pyrimidine have been
investigated from the ultrasonic velocity and density measurements at
different concentration and different % in dioxane-water mixture at
305K. The adiabatic compressibility (βs), acoustic impedance (Z),
intermolecular free length (Lf), apparent molar volume(ϕv) and
relative association (RA) values have been calculated from the
experimental data of velocity and density measurement at
concentration range of 0.01- 0.000625 mol/lit and 70%,75% and 80%
dioxane water mixture. These above parameters are used to discuss
the structural and molecular interactions.
Abstract: Traditional multivariate control charts assume that measurement from manufacturing processes follows a multivariate normal distribution. However, this assumption may not hold or may be difficult to verify because not all the measurement from manufacturing processes are normal distributed in practice. This study develops a new multivariate control chart for monitoring the processes with non-normal data. We propose a mechanism based on integrating the one-class classification method and the adaptive technique. The adaptive technique is used to improve the sensitivity to small shift on one-class classification in statistical process control. In addition, this design provides an easy way to allocate the value of type I error so it is easier to be implemented. Finally, the simulation study and the real data from industry are used to demonstrate the effectiveness of the propose control charts.
Abstract: The study and development of an innovative material
for building insulation is really important for a sustainable society in order to improve comfort and reducing energy consumption. The aim of this work is the development of insulating panels for
sustainable buildings based on an innovative material made by
cardboard and Phase Change Materials (PCMs).
The research has consisted in laboratory tests whose purpose has been the obtaining of the required properties for insulation panels: lightweight, porous structures and mechanical resistance. PCMs have been used for many years in the building industry as
smart insulation technology because of their properties of storage and release high quantity of latent heat at useful specific temperatures [1]- [2].
The integration of PCMs into cellulose matrix during the waste paper recycling process has been developed in order to obtain a
composite material.
Experiments on the productive process for the realization of insulating panels were done in order to make the new material
suitable for building application. The addition of rising agents
demonstrated the possibility to obtain a lighter structure with better
insulation properties.
Several tests were conducted to verify the new panel properties. The results obtained have shown the possibility to realize an
innovative and sustainable material suitable to replace insulating panels currently used.
Abstract: Iron ore and coal are the two major important raw
materials being used in Iron making industries. Usually ore fines
containing around 5% Alumina are rejected due to higher proportion
of alumina. Therefore, a technology or process which may reduce
the alumina content by 2% by beneficiation process will be highly
attractive . In addition fine coals with ash content is used nearly 12%
is directly injected in blast furnace. Fast fluidization is a technology
by using dry beneficiation of coal and iron ore can be done. During
the fluidization process the iron ore band coal is fluidized at high
velocity in the riser of a fast fluidized bed, the heavier and coarse
particles is generally settled at the bottom in a dense zone of the riser
while the finer and lighter particle are entrained to the top dilute zone
and then via a cyclone is fed back to the bottom of the riser column.
Most of the alumina and low ash fine size coals being lighter are
expected to move up to the riser and by a natural beneficiation of
ores is expected to take place in the riser. Therefore in this study an
attempt has been made for dry beneficiation of iron ore and coal in a
fluidized bed and its hydrodynamic characterization.
Abstract: This paper presents a new method of fault detection and isolation (FDI) for polymer electrolyte membrane (PEM) fuel cell (FC) dynamic systems under an open-loop scheme. This method uses a radial basis function (RBF) neural network to perform fault identification, classification and isolation. The novelty is that the RBF model of independent mode is used to predict the future outputs of the FC stack. One actuator fault, one component fault and three sensor faults have been introduced to the PEMFC systems experience faults between -7% to +10% of fault size in real-time operation. To validate the results, a benchmark model developed by Michigan University is used in the simulation to investigate the effect of these five faults. The developed independent RBF model is tested on MATLAB R2009a/Simulink environment. The simulation results confirm the effectiveness of the proposed method for FDI under an open-loop condition. By using this method, the RBF networks able to detect and isolate all five faults accordingly and accurately.
Abstract: In two studies we tested the hypothesis that the
appropriate linguistic formulation of a deontic rule – i.e. the
formulation which clarifies the monadic nature of deontic operators
- should produce more correct responses than the conditional
formulation in Wason selection task. We tested this assumption by
presenting a prescription rule and a prohibition rule in conditional
vs. proper deontic formulation. We contrasted this hypothesis with
two other hypotheses derived from social contract theory and
relevance theory. According to the first theory, a deontic rule
expressed in terms of cost-benefit should elicit a cheater detection
module, sensible to mental states attributions and thus able to
discriminate intentional rule violations from accidental rule
violations. We tested this prevision by distinguishing the two types
of violations. According to relevance theory, performance in
selection task should improve by increasing cognitive effect and
decreasing cognitive effort. We tested this prevision by focusing
experimental instructions on the rule vs. the action covered by the
rule. In study 1, in which 480 undergraduates participated, we
tested these predictions through a 2 x 2 x 2 x 2 (type of the rule x
rule formulation x type of violation x experimental instructions)
between-subjects design. In study 2 – carried out by means of a 2 x
2 (rule formulation x type of violation) between-subjects design -
we retested the hypothesis of rule formulation vs. the cheaterdetection
hypothesis through a new version of selection task in
which intentional vs. accidental rule violations were better
discriminated. 240 undergraduates participated in this study.
Results corroborate our hypothesis and challenge the contrasting
assumptions. However, they show that the conditional formulation
of deontic rules produces a lower performance than what is
reported in literature.
Abstract: In this paper, we introduce a new method for elliptical
object identification. The proposed method adopts a hybrid scheme
which consists of Eigen values of covariance matrices, Circular
Hough transform and Bresenham-s raster scan algorithms. In this
approach we use the fact that the large Eigen values and small Eigen
values of covariance matrices are associated with the major and minor
axial lengths of the ellipse. The centre location of the ellipse can be
identified using circular Hough transform (CHT). Sparse matrix
technique is used to perform CHT. Since sparse matrices squeeze zero
elements and contain a small number of nonzero elements they
provide an advantage of matrix storage space and computational time.
Neighborhood suppression scheme is used to find the valid Hough
peaks. The accurate position of circumference pixels is identified
using raster scan algorithm which uses the geometrical symmetry
property. This method does not require the evaluation of tangents or
curvature of edge contours, which are generally very sensitive to
noise working conditions. The proposed method has the advantages of
small storage, high speed and accuracy in identifying the feature. The
new method has been tested on both synthetic and real images.
Several experiments have been conducted on various images with
considerable background noise to reveal the efficacy and robustness.
Experimental results about the accuracy of the proposed method,
comparisons with Hough transform and its variants and other
tangential based methods are reported.
Abstract: Experiments with pumpkin-rowanberry marmalade
candies were carried out at the Faculty of Food Technology of the
Latvia University of Agriculture. The objective of this investigation
was to evaluate the quality changes of pumpkin-rowanberry
marmalade candies packed in different packaging materials during
the storage of 15 weeks, and to find the most suitable packaging
material for prolongation of low sugar marmalade candies shelf-life.
An active packaging in combination with modified atmosphere
(MAP, CO2 100%) was examined and compared with traditional
packaging in air ambiance. Polymer Multibarrier 60 and paper bags
were used. Influence of iron based oxygen absorber in sachets of 500
cc obtained from Mitsubishi Gas Chemical Europe Ageless® on the
marmalade candies’ quality was tested during shelf life. Samples of
80±5 g were packaged in polymer pouches (110 mm x 110 mm),
hermetically sealed by MULTIVAC C300 vacuum chamber machine,
and stored in a room temperature +21±0.5 °C. The physiochemical
properties –moisture content, hardness, aw, pH, changes of
atmosphere content (CO2 and O2), ascorbic acid, total carotenoids,
total phenols in headspace of packs, and microbial conditions were
analysed before packaging and in the 1st, 3rd , 5th, 8th, 11th and 15th
weeks of storage.
Abstract: This paper proposes a novel solution for optimizing
the size and communication overhead of a distributed multiagent
system without compromising the performance. The proposed approach
addresses the challenges of scalability especially when the
multiagent system is large. A modified spectral clustering technique
is used to partition a large network into logically related clusters.
Agents are assigned to monitor dedicated clusters rather than monitor
each device or node. The proposed scalable multiagent system is
implemented using JADE (Java Agent Development Environment)
for a large power system. The performance of the proposed topologyindependent
decentralized multiagent system and the scalable multiagent
system is compared by comprehensively simulating different
fault scenarios. The time taken for reconfiguration, the overall computational
complexity, and the communication overhead incurred are
computed. The results of these simulations show that the proposed
scalable multiagent system uses fewer agents efficiently, makes faster
decisions to reconfigure when a fault occurs, and incurs significantly
less communication overhead.
Abstract: Business rules and data warehouse are concepts and
technologies that impact a wide variety of organizational tasks. In
general, each area has evolved independently, impacting application
development and decision-making. Generating knowledge from data
warehouse is a complex process. This paper outlines an approach to
ease import of information and knowledge from a data warehouse
star schema through an inference class of business rules. The paper
utilizes the Oracle database for illustrating the working of the
concepts. The star schema structure and the business rules are stored
within a relational database. The approach is explained through a
prototype in Oracle-s PL/SQL Server Pages.
Abstract: This paper describes a code clone visualization method, called FC graph, and the implementation issues. Code clone detection tools usually show the results in a textual representation. If the results are large, it makes a problem to software maintainers with understanding them. One of the approaches to overcome the situation is visualization of code clone detection results. A scatter plot is a popular approach to the visualization. However, it represents only one-to-one correspondence and it is difficult to find correspondence of code clones over multiple files. FC graph represents correspondence among files, code clones and packages in Java. All nodes in FC graph are positioned using force-directed graph layout, which is dynami- cally calculated to adjust the distances of nodes until stabilizing them. We applied FC graph to some open source programs and visualized the results. In the author’s experience, FC graph is helpful to grasp correspondence of code clones over multiple files and also code clones with in a file.