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: Implementing quality assurance in higher education establishments is the main focus of the reform process currently undertaken by the Ministry of Higher Education and Scientific Research in the Kurdistan Region of Iraq. The reform agenda has involved attempts to improve academic quality and management processes in universities, technical institutions and colleges. The central challenge for the reform process is to produce change in higher education in a region where administration is described as centralized and bureaucratic. To make these changes, there should be a well-designed plans and follow up processes in order to monitor progress and develop responses to obstacles. Lack of skills, resources, political dilemmas, poor motivation, and readiness to face the consequences of change are factors which will determine the success of the reform process.
Abstract: The k-nearest neighbors (knn) is a simple but effective method of classification. In this paper we present an extended version of this technique for chemical compounds used in High Throughput Screening, where the distances of the nearest neighbors can be taken into account. Our algorithm uses kernel weight functions as guidance for the process of defining activity in screening data. Proposed kernel weight function aims to combine properties of graphical structure and molecule descriptors of screening compounds. We apply the modified knn method on several experimental data from biological screens. The experimental results confirm the effectiveness of the proposed method.
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: 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: In the present work we investigate both the elastic and
electric properties of a chiral material. We consider a composite
structure made from a polymer matrix and anisotropic inclusions of
GaAs taking into account piezoelectric and dielectric properties of
the composite material. The principal task of the work is the
estimation of the functional properties of the composite material.
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: Web applications have become complex and crucial for many firms, especially when combined with areas such as CRM (Customer Relationship Management) and BPR (Business Process Reengineering). The scientific community has focused attention to Web application design, development, analysis, testing, by studying and proposing methodologies and tools. Static and dynamic techniques may be used to analyze existing Web applications. The use of traditional static source code analysis may be very difficult, for the presence of dynamically generated code, and for the multi-language nature of the Web. Dynamic analysis may be useful, but it has an intrinsic limitation, the low number of program executions used to extract information. Our reverse engineering analysis, used into our WAAT (Web Applications Analysis and Testing) project, applies mutational techniques in order to exploit server side execution engines to accomplish part of the dynamic analysis. This paper studies the effects of mutation source code analysis applied to Web software to build application models. Mutation-based generated models may contain more information then necessary, so we need a pruning mechanism.
Abstract: This study aims to screen out and to optimize the
major nutrients for maximum carotenoid production and
antioxidation characteristics by Rhodotorula rubra. It was found that
supplementary of 10 g/l glucose as carbon source, 1 g/l ammonium
sulfate as nitrogen source and 1 g/l yeast extract as growth factor in
the medium provided the better yield of carotenoid content of 30.39
μg/g cell dry weight the amount of antioxidation of Rhodotorula
rubra by DPPH, ABTS and MDA method were 1.463%, 34.21% and
34.09 μmol/l, respectively.
Abstract: Environmental awareness and the recent
environmental policies have forced many electric utilities to
restructure their operational practices to account for their emission
impacts. One way to accomplish this is by reformulating the
traditional economic dispatch problem such that emission effects are
included in the mathematical model. This paper presents a Particle
Swarm Optimization (PSO) algorithm to solve the Economic-
Emission Dispatch problem (EED) which gained recent attention due
to the deregulation of the power industry and strict environmental
regulations. The problem is formulated as a multi-objective one with
two competing functions, namely economic cost and emission
functions, subject to different constraints. The inequality constraints
considered are the generating unit capacity limits while the equality
constraint is generation-demand balance. A novel equality constraint
handling mechanism is proposed in this paper. PSO algorithm is
tested on a 30-bus standard test system. Results obtained show that
PSO algorithm has a great potential in handling multi-objective
optimization problems and is capable of capturing Pareto optimal
solution set under different loading conditions.
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: Product Data Management (PDM) systems for Computer
Aided Design (CAD) file management are widely established
in design processes. This management system is indispensable for
design collaboration or when design task distribution is present. It is
thus surprising that engineering design curricula has not paid much
attention in the education of PDM systems. This is also the case
for eduction of ecodesign and environmental evaluation of products.
With the rise of sustainability as a strategic aspect in companies,
environmental concerns are becoming a key issue in design. This
paper discusses the establishment of a PDM platform to be used
among technical and vocational schools in Austria. The PDM system
facilitates design collaboration among these schools. Further, it will
be discussed how the PDM system has been prepared in order to
facilitate environmental evaluation of parts, components and subassemblies
of a product. By integrating a Business Intelligence
solution, environmental Life Cycle Assessment and communication
of results is enabled.
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.
Abstract: This study explores how the mechanics of learning
paves the way to engineering innovation. Theories related to learning
in the new product/service innovation are reviewed from an
organizational perspective, behavioral perspective, and engineering
perspective. From this, an engineering team-s external interactions
for knowledge brokering and internal composition for skill balance
are examined from a learning and innovation viewpoints. As a result,
an integrated learning model is developed by reconciling the
theoretical perspectives as well as developing propositions that
emphasize the centrality of learning, and its drivers, in the
engineering product/service development. The paper also provides a
review and partial validation of the propositions using the results of a
previously published field study in the aerospace industry.
Abstract: Imperfect transmission conditions modeling a thin reactive 2D interphases layer between two dissimilar bonded strips have been extracted. In this paper, the soundness of these transmission conditions for heat conduction problems are examined by the finite element method for a strong temperature-dependent source or sink and non-monotonic temperature distributions around the faces..