Abstract: Cluster analysis is the name given to a diverse collection of techniques that can be used to classify objects (e.g. individuals, quadrats, species etc). While Kohonen's Self-Organizing Feature Map (SOFM) or Self-Organizing Map (SOM) networks have been successfully applied as a classification tool to various problem domains, including speech recognition, image data compression, image or character recognition, robot control and medical diagnosis, its potential as a robust substitute for clustering analysis remains relatively unresearched. SOM networks combine competitive learning with dimensionality reduction by smoothing the clusters with respect to an a priori grid and provide a powerful tool for data visualization. In this paper, SOM is used for creating a toroidal mapping of two-dimensional lattice to perform cluster analysis on results of a chemical analysis of wines produced in the same region in Italy but derived from three different cultivators, referred to as the “wine recognition data" located in the University of California-Irvine database. The results are encouraging and it is believed that SOM would make an appealing and powerful decision-support system tool for clustering tasks and for data visualization.
Abstract: Multicast Network Technology has pervaded our
lives-a few examples of the Networking Techniques and also for the
improvement of various routing devices we use. As we know the
Multicast Data is a technology offers many applications to the user
such as high speed voice, high speed data services, which is presently
dominated by the Normal networking and the cable system and
digital subscriber line (DSL) technologies. Advantages of Multi cast
Broadcast such as over other routing techniques. Usually QoS
(Quality of Service) Guarantees are required in most of Multicast
applications. The bandwidth-delay constrained optimization and we
use a multi objective model and routing approach based on genetic
algorithm that optimizes multiple QoS parameters simultaneously.
The proposed approach is non-dominated routes and the performance
with high efficiency of GA. Its betterment and high optimization has
been verified. We have also introduced and correlate the result of
multicast GA with the Broadband wireless to minimize the delay in
the path.
Abstract: Electrophoretic motion of a liquid droplet within an
uncharged cylindrical pore is investigated theoretically in this study. It
is found that the boundary effect in terms of the reduction of droplet
mobility (droplet velocity per unit strength of the applied electric field)
is very significant when the double layer surrounding the droplet is
thick, and diminishes as it gets very thin. Moreover, the viscosity ratio
of the ambient fluid to the internal one, σ, is a crucial factor in
determining its electrophoretic behavior. The boundary effect is less
significant as the viscosity ratio gets high. Up to 70% mobility
reduction is observed when this ratio is low (σ = 0.01), whereas only
40% reduction when it is high (σ = 100). The results of this study can
be utilized in various fields of biotechnology, such as a biosensor or a
lab-on-a-chip device.
Abstract: The paper presents the influence of the conventional
ploughing tillage technology in comparison with the minimum
tillage, upon the soil properties, weed control and yield in the case of
maize (Zea mays L.), soya-bean (Glycine hispida L.) and winter
wheat (Triticum aestivum L.) in a three years crop rotation. A
research has been conducted at the University of Agricultural
Sciences and Veterinary Medicine Cluj-Napoca, Romania. The use of
minimum soil tillage systems within a three years rotation: maize,
soya-bean, wheat favorites the rise of the aggregates hydro stability
with 5.6-7.5% on a 0-20 cm depth and 5-11% on 20-30 cm depth.
The minimum soil tillage systems – paraplow, chisel or rotary grape
– are polyvalent alternatives for basic preparation, germination bed
preparation and sowing, for fields and crops with moderate loose
requirements being optimized technologies for: soil natural fertility
activation and rationalization, reduction of erosion, increasing the
accumulation capacity for water and realization of sowing in the
optimal period. The soil tillage system influences the productivity
elements of cultivated species and finally the productions thus
obtained. Thus, related to conventional working system, the
productions registered in minimum tillage working represented 89-
97% in maize, 103-112% in soya-bean, 93-99% in winter-wheat. The
results of investigations showed that the yield is a conclusion soil
tillage systems influence on soil properties, plant density assurance
and on weed control. Under minimum tillage systems in the case of
winter weat as an option for replacing classic ploughing, the best
results in terms of quality indices were obtained from version worked
with paraplow, followed by rotary harrow and chisel. At variants
worked with paraplow were obtained quality indices close to those of
the variant worked with plow, and protein and gluten content was
even higher. At Ariesan variety, highest protein content, 12.50% and
gluten, 28.6% was obtained for the variant paraplow.
Abstract: The customary practice of identifying industrial sickness is a set traditional techniques which rely upon a range of manual monitoring and compilation of financial records. It makes the process tedious, time consuming and often are susceptible to manipulation. Therefore, certain readily available tools are required which can deal with such uncertain situations arising out of industrial sickness. It is more significant for a country like India where the fruits of development are rarely equally distributed. In this paper, we propose an approach based on Artificial Neural Network (ANN) to deal with industrial sickness with specific focus on a few such units taken from a less developed north-east (NE) Indian state like Assam. The proposed system provides decision regarding industrial sickness using eight different parameters which are directly related to the stages of sickness of such units. The mechanism primarily uses certain signals and symptoms of industrial health to decide upon the state of a unit. Specifically, we formulate an ANN based block with data obtained from a few selected units of Assam so that required decisions related to industrial health could be taken. The system thus formulated could become an important part of planning and development. It can also contribute towards computerization of decision support systems related to industrial health and help in better management.
Abstract: Titanium nitride (TiN) has been synthesized using the
sheet plasma negative ion source (SPNIS). The parameters used for
its effective synthesis has been determined from previous
experiments and studies. In this study, further enhancement of the
deposition rate of TiN synthesis and advancement of the SPNIS
operation is presented. This is primarily achieved by the addition of
Sm-Co permanent magnets and a modification of the configuration in
the TiN deposition process. The magnetic enhancement is aimed at
optimizing the sputtering rate and the sputtering yield of the process.
The Sm-Co permanent magnets are placed below the Ti target for
better sputtering by argon. The Ti target is biased from –250V to –
350V and is sputtered by Ar plasma produced at discharge current of
2.5–4A and discharge potential of 60–90V. Steel substrates of
dimensions 20x20x0.5mm3 were prepared with N2:Ar volumetric
ratios of 1:3, 1:5 and 1:10. Ocular inspection of samples exhibit
bright gold color associated with TiN. XRD characterization
confirmed the effective TiN synthesis as all samples exhibit the (200)
and (311) peaks of TiN and the non-stoichiometric Ti2N (220) facet.
Cross-sectional SEM results showed increase in the TiN deposition
rate of up to 0.35μm/min. This doubles what was previously obtained
[1]. Scanning electron micrograph results give a comparative
morphological picture of the samples. Vickers hardness results gave
the largest hardness value of 21.094GPa.
Abstract: Because of importance of energy, optimization of
power generation systems is necessary. Gas turbine cycles are
suitable manner for fast power generation, but their efficiency is
partly low. In order to achieving higher efficiencies, some
propositions are preferred such as recovery of heat from exhaust
gases in a regenerator, utilization of intercooler in a multistage
compressor, steam injection to combustion chamber and etc.
However thermodynamic optimization of gas turbine cycle, even
with above components, is necessary. In this article multi-objective
genetic algorithms are employed for Pareto approach optimization of
Regenerative-Intercooling-Gas Turbine (RIGT) cycle. In the multiobjective
optimization a number of conflicting objective functions
are to be optimized simultaneously. The important objective
functions that have been considered for optimization are entropy
generation of RIGT cycle (Ns) derives using Exergy Analysis and
Gouy-Stodola theorem, thermal efficiency and the net output power
of RIGT Cycle. These objectives are usually conflicting with each
other. The design variables consist of thermodynamic parameters
such as compressor pressure ratio (Rp), excess air in combustion
(EA), turbine inlet temperature (TIT) and inlet air temperature (T0).
At the first stage single objective optimization has been investigated
and the method of Non-dominated Sorting Genetic Algorithm
(NSGA-II) has been used for multi-objective optimization.
Optimization procedures are performed for two and three objective
functions and the results are compared for RIGT Cycle. In order to
investigate the optimal thermodynamic behavior of two objectives,
different set, each including two objectives of output parameters, are
considered individually. For each set Pareto front are depicted. The
sets of selected decision variables based on this Pareto front, will
cause the best possible combination of corresponding objective
functions. There is no superiority for the points on the Pareto front
figure, but they are superior to any other point. In the case of three
objective optimization the results are given in tables.
Abstract: For complete support of Quality of Service, it is better that environment itself predicts resource requirements of a job by using special methods in the Grid computing. The exact and correct prediction causes exact matching of required resources with available resources. After the execution of each job, the used resources will be saved in the active database named "History". At first some of the attributes will be exploit from the main job and according to a defined similarity algorithm the most similar executed job will be exploited from "History" using statistic terms such as linear regression or average, resource requirements will be predicted. The new idea in this research is based on active database and centralized history maintenance. Implementation and testing of the proposed architecture results in accuracy percentage of 96.68% to predict CPU usage of jobs and 91.29% of memory usage and 89.80% of the band width usage.
Abstract: A two-dimensional moving mesh algorithm is developed to simulate the general motion of two rotating bodies with relative translational motion. The grid includes a background grid and two sets of grids around the moving bodies. With this grid arrangement rotational and translational motions of two bodies are handled separately, with no complications. Inter-grid boundaries are determined based on their distances from two bodies. In this method, the overset concept is applied to hybrid grid, and flow variables are interpolated using a simple stencil. To evaluate this moving mesh algorithm unsteady Euler flow is solved for different cases using dual-time method of Jameson. Numerical results show excellent agreement with experimental data and other numerical results. To demonstrate the capability of present algorithm for accurate solution of flow fields around moving bodies, some benchmark problems have been defined in this paper.
Abstract: This study was conducted to evaluate the antifungal
activities of Cinnamomum zeylanicum and Origanum vulgare L.
essential oil against Aspergillus flavus in culture media and tomato
paste. 200 ppm of cinnamon and 500 ppm of oregano completely
inhibited A. flavus growth in culture media, while in tomato paste 300
ppm of cinnamon and 200 ppm of oregano had the same effect. Test
panel evaluations revealed that samples with 100 and 200 ppm
cinnamon were acceptable. The results may suggest the potential use
of Cinnamomum zeylanicum essential oil as natural preservative in
tomato paste.
Abstract: This study examined the underlying dimensions of
brand equity in the chocolate industry. For this purpose, researchers
developed a model to identify which factors are influential in
building brand equity. The second purpose was to assess brand
loyalty and brand images mediating effect between brand attitude,
brand personality, brand association with brand equity. The study
employed structural equation modeling to investigate the causal
relationships between the dimensions of brand equity and brand
equity itself. It specifically measured the way in which consumers’
perceptions of the dimensions of brand equity affected the overall
brand equity evaluations. Data were collected from a sample of
consumers of chocolate industry in Iran. The results of this empirical
study indicate that brand loyalty and brand image are important
components of brand equity in this industry. Moreover, the role of
brand loyalty and brand image as mediating factors in the intention of
brand equity are supported. The principal contribution of the present
research is that it provides empirical evidence of the
multidimensionality of consumer based brand equity, supporting
Aaker´s and Keller´s conceptualization of brand equity. The present
research also enriched brand equity building by incorporating the
brand personality and brand image, as recommended by previous
researchers. Moreover, creating the brand equity index in chocolate
industry of Iran particularly is novel.
Abstract: The present study aims at determining the effect of ageing on the impact toughness and microstructure of 2024 Al-Cu - Mg alloy. Following the 2 h solutionizing treatment at 450°C and water quench, the specimens were aged at 200°C for various periods (1 to 18 h). The precipitation stages during ageing were monitored by hardness measurements. For each specimen group, Charpy impact and hardness tests were carried out. During ageing the impact toughness of the alloy first increased, and then, following a maxima decreased due to the precipitation of intermediate phases, finally it reached its minimum at the peak hardness. Correlations between hardness and impact toughness were investigated.
Abstract: Competitive relationships among Bradyrhizobium
japonicum USDA serogroup 123, 122 and 138 were screened versus
the standard commercial soybean variety Williams and two
introductions P1 377578 "671" in a field trial. Displacement of strain
123 by an effective strain should improved N2 fixation. Root nodules
were collected and strain occupancy percentage was determined
using strain specific fluorescent antibodies technique. As anticipated
the strain USDA 123 dominated 92% of nodules due to the high
affinity between the host and the symbiont. This dominance was
consistent and not changed materially either by inoculation practice
or by introducing new strainan. The interrelationship between the
genotype Williams and serogroup 122 & 138 was found very weak
although the cell density of the strain in the rhizosphere area was
equal. On the other hand, the nodule occupancy of genotypes 671 and
166 with rhizobia serogroup 123 was almost diminished to zero. .
The data further exhibited that the genotypes P1 671 and P1 166 have
high affinity to colonize with strains 122 and 138 whereas Williams
was highly promiscuous to strain 123.
Abstract: Stair climbing is one of critical issues for field robots to
widen applicable areas. This paper presents optimal design on
kinematic parameters of a new robotic platform for stair climbing. The
robotic platform climbs various stairs by body flip locomotion with
caterpillar type main platform. Kinematic parameters such as platform
length, platform height, and caterpillar rotation speed are optimized to
maximize stair climbing stability. Three types of stairs are used to
simulate typical user conditions. The optimal design process is
conducted based on Taguchi methodology, and resulting parameters
with optimized objective function are presented. In near future, a
prototype is assembled for real environment testing.
Abstract: This paper presents a critical study about the
application of Neural Networks to ion-exchange process. Ionexchange
is a complex non-linear process involving many factors
influencing the ions uptake mechanisms from the pregnant solution.
The following step includes the elution. Published data presents
empirical isotherm equations with definite shortcomings resulting in
unreliable predictions. Although Neural Network simulation
technique encounters a number of disadvantages including its “black
box", and a limited ability to explicitly identify possible causal
relationships, it has the advantage to implicitly handle complex
nonlinear relationships between dependent and independent
variables. In the present paper, the Neural Network model based on
the back-propagation algorithm Levenberg-Marquardt was developed
using a three layer approach with a tangent sigmoid transfer function
(tansig) at hidden layer with 11 neurons and linear transfer function
(purelin) at out layer. The above mentioned approach has been used
to test the effectiveness in simulating ion exchange processes. The
modeling results showed that there is an excellent agreement between
the experimental data and the predicted values of copper ions
removed from aqueous solutions.
Abstract: With deep development of software reuse, componentrelated
technologies have been widely applied in the development of
large-scale complex applications. Component identification (CI) is
one of the primary research problems in software reuse, by analyzing
domain business models to get a set of business components with high
reuse value and good reuse performance to support effective reuse.
Based on the concept and classification of CI, its technical stack is
briefly discussed from four views, i.e., form of input business models,
identification goals, identification strategies, and identification
process. Then various CI methods presented in literatures are
classified into four types, i.e., domain analysis based methods,
cohesion-coupling based clustering methods, CRUD matrix based
methods, and other methods, with the comparisons between these
methods for their advantages and disadvantages. Additionally, some
insufficiencies of study on CI are discussed, and the causes are
explained subsequently. Finally, it is concluded with some
significantly promising tendency about research on this problem.
Abstract: This article is an extension and a practical application
approach of Wheeler-s NEBIC theory (Net Enabled Business
Innovation Cycle). NEBIC theory is a new approach in IS research
and can be used for dynamic environment related to new technology.
Firms can follow the market changes rapidly with support of the IT
resources. Flexible firms adapt their market strategies, and respond
more quickly to customers changing behaviors. When every leading
firm in an industry has access to the same IT resources, the way that
these IT resources are managed will determine the competitive
advantages or disadvantages of firm. From Dynamic Capabilities
Perspective and from newly introduced NEBIC theory by Wheeler,
we know that only IT resources cannot deliver customer value but
good configuration of those resources can guarantee customer value
by choosing the right emerging technology, grasping the economic
opportunities through business innovation and growth. We found
evidences in literature that SOA (Service Oriented Architecture) is a
promising emerging technology which can deliver the desired
economic opportunity through modularity, flexibility and loosecoupling.
SOA can also help firms to connect in network which can
open a new window of opportunity to collaborate in innovation and
right kind of outsourcing
Abstract: In this paper, a class of recurrent neural networks (RNNs) with variable delays are studied on almost periodic time scales, some sufficient conditions are established for the existence and global exponential stability of the almost periodic solution. These results have important leading significance in designs and applications of RNNs. Finally, two examples and numerical simulations are presented to illustrate the feasibility and effectiveness of the results.
Abstract: This article examines the emergence and development
of the Kazakhstan species of humanism. The biggest challenge for
Kazakhstan in terms of humanism is connected with advocating
human values in parallel to promoting national interests; preserving
the continuity of traditions in various spheres of life, business and
culture. This should be a common goal for the entire society, the
main direction for a national intelligence, and a platform for the state
policy. An idea worth considering is a formation of national humanist
tradition model; the challenges are adapting people to live in the
context of new industrial and innovative economic conditions,
keeping the balance during intensive economic development of the
country, and ensuring social harmony in the society.
Abstract: To explore pipelines is one of various bio-mimetic
robot applications. The robot may work in common buildings such as
between ceilings and ducts, in addition to complicated and massive
pipeline systems of large industrial plants. The bio-mimetic robot finds
any troubled area or malfunction and then reports its data. Importantly,
it can not only prepare for but also react to any abnormal routes in the
pipeline. The pipeline monitoring tasks require special types of mobile
robots. For an effective movement along a pipeline, the movement of
the robot will be similar to that of insects or crawling animals. During
its movement along the pipelines, a pipeline monitoring robot has an
important task of finding the shapes of the approaching path on the
pipes. In this paper we propose an effective solution to the pipeline
pattern recognition, based on the fuzzy classification rules for the
measured IR distance data.