Abstract: Mustard leaves are rich in folates, vitamin A, K and
B-complex. Mustard greens are low in calories and fats and rich in
dietary fiber. They are rich in potassium, manganese, iron, copper,
calcium, magnesium and low in sodium. It is very rich in antioxidants
and Phytonutrients. For the optimization of process variables
(moisture content and mustard leave powder), the experiments were
conducted according to central composite Face Centered Composite
design of RSM. The mustard leaves powder was replaced with
composite flour (a combination of rice, chickpea and corn in the ratio
of 70:15:15). The extrudate was extruded in a twin screw extruder at
a barrel temperature of 120°C. The independent variables were
mustard leaves powder (2-10 %) and moisture content (12-20 %).
Responses analyzed were bulk density, water solubility index, water
absorption index, lateral expansion, antioxidant activity, total
phenolic content, and overall acceptability. The optimum conditions
obtained were 7.19 g mustard leaves powder in 100g premix having
16.8% moisture content (w.b).
Abstract: This paper presents Carrier Sense Multiple Access
(CSMA) communication models based on SoC design methodology.
Such a model can be used to support the modeling of the complex
wireless communication systems. Therefore, the use of such
communication model is an important technique in the construction
of high-performance communication. SystemC has been chosen
because it provides a homogeneous design flow for complex designs
(i.e. SoC and IP-based design). We use a swarm system to validate
CSMA designed model and to show how advantages of incorporating
communication early in the design process. The wireless
communication created through the modeling of CSMA protocol that
can be used to achieve communication between all the agents and to
coordinate access to the shared medium (channel).
Abstract: This paper presents an application of a “Systematic
Soft Domain Driven Design Framework” as a soft systems approach
to domain-driven design of information systems development. The
framework use SSM as a guiding methodology within which we have
embedded a sequence of design tasks based on the UML leading to
the implementation of a software system using the Naked Objects
framework. This framework have been used in action research
projects that have involved the investigation and modelling of
business processes using object-oriented domain models and the
implementation of software systems based on those domain models.
Within this framework, Soft Systems Methodology (SSM) is used as
a guiding methodology to explore the problem situation and to
develop the domain model using UML for the given business
domain. The framework is proposed and evaluated in our previous
works, and a real case study “Information Retrieval System for
academic research” is used, in this paper, to show further practice and
evaluation of the framework in different business domain. We argue
that there are advantages from combining and using techniques from
different methodologies in this way for business domain modelling.
The framework is overviewed and justified as multimethodology
using Mingers multimethodology ideas.
Abstract: Model transformation, as a pivotal aspect of Modeldriven
engineering, attracts more and more attentions both from
researchers and practitioners. Many domains (enterprise engineering,
software engineering, knowledge engineering, etc.) use model
transformation principles and practices to serve to their domain
specific problems; furthermore, model transformation could also be
used to fulfill the gap between different domains: by sharing and
exchanging knowledge. Since model transformation has been widely
used, there comes new requirement on it: effectively and efficiently
define the transformation process and reduce manual effort that
involved in. This paper presents an automatic model transformation
methodology based on semantic and syntactic comparisons, and
focuses particularly on granularity issue that existed in transformation
process. Comparing to the traditional model transformation
methodologies, this methodology serves to a general purpose: crossdomain
methodology. Semantic and syntactic checking
measurements are combined into a refined transformation process,
which solves the granularity issue. Moreover, semantic and syntactic
comparisons are supported by software tool; manual effort is replaced
in this way.
Abstract: Roadway planning and design is a very complex
process involving five key phases before a project is completed;
planning, project development, final design, right-of-way, and
construction. The planning phase for a new roadway transportation
project is a very critical phase as it greatly affects all latter phases of
the project. A location study is usually performed during the
preliminary planning phase in a new roadway project. The objective
of the location study is to develop alignment alternatives that are cost
efficient considering land acquisition and construction costs. This
paper describes a methodology to develop optimal preliminary
roadway alignments utilizing spatial-data. Four optimization criteria
are taken into consideration; roadway length, land cost, land slope,
and environmental impacts. The basic concept of the methodology is
to convert the proposed project area into a grid, which represents the
search space for an optimal alignment. The aforementioned
optimization criteria are represented in each of the grid’s cells. A
spatial-data optimization technique is utilized to find the optimal
alignment in the search space based on the four optimization criteria.
Two case studies for new roadway projects in Duval County in the
State of Florida are presented to illustrate the methodology. The
optimization output alignments are compared to the proposed Florida
Department of Transportation (FDOT) alignments. The comparison is
based on right-of-way costs for the alignments. For both case studies,
the right-of-way costs for the developed optimal alignments were
found to be significantly lower than the FDOT alignments.
Abstract: Rice straw is lignocellulosic biomass which can be utilized as substrate for the biogas production. However, due to the property and composition of rice straw, it is difficult to be degraded by hydrolysis enzymes. One of the pretreatment methods that modify such properties of lignocellulosic biomass is the application of lignocellulose-degrading microbial consortia. The aim of this study is to investigate the effect of microbial consortia to enhance biogas production. To select the high efficient consortium, cellulase enzymes were extracted and their activities were analyzed. The results suggested that microbial consortium culture obtained from cattle manure is the best candidate compared to decomposed wood and horse manure. A microbial consortium isolated from cattle manure was then mixed with anaerobic sludge and used as inoculum for biogas production. The optimal conditions for biogas production were investigated using response surface methodology (RSM). The tested parameters were the ratio of amount of microbial consortium isolated and amount of anaerobic sludge (MI:AS), substrate to inoculum ratio (S:I) and temperature. Here, the value of the regression coefficient R2 = 0.7661 could be explained by the model which is high to advocate the significance of the model. The highest cumulative biogas yield was 104.6 ml/g-rice straw at optimum ratio of MI:AS, ratio of S:I, and temperature of 2.5:1, 15:1 and 44°C respectively.
Abstract: This technical contribution treats of a novel approach
to condition-oriented maintenance as elaborated by Collaborative
Research Centre 653 at the Leibniz University in Hanover. The
objective resides in the targeted analysis of information about a
component's lifecycle for maintenance purposes. The information in
question is collected by means of the Collaborative Research Centre's
innovative technologies. This enables preventive maintenance of
components on the basis of their condition. This contribution initially
explains condition-oriented maintenance, before introducing the
Collaborative Research Centre and finally presenting the
methodology for analyzing the information. The current state of
development is described and an outlook provided for expanding the
methodology.
Abstract: The paper deals with behaviour of the segment 50+ in
the financial market in the Czech Republic. This segment could be
said as the strong market power and it can be a crucial business
potential for financial business units. The main defined objective of
this paper is analysis of the customers´ behaviour of the segment 50-
60 years in the financial market in the Czech Republic and proposal
making of the suitable marketing approach to satisfy their demands in
the area of product, price, distribution and marketing communication
policy. This paper is based on data from one part of primary
marketing research. Paper determinates the basic problem areas as
well as definition of financial services marketing, defining the
primary research problem, hypothesis and primary research
methodology. Finally suitable marketing approach to selected sub
segment at age of 50-60 years is proposed according to marketing
research findings.
Abstract: The present work analyses different parameters of end
milling to minimize the surface roughness for AISI D2 steel. D2 Steel
is generally used for stamping or forming dies, punches, forming
rolls, knives, slitters, shear blades, tools, scrap choppers, tyre
shredders etc. Surface roughness is one of the main indices that
determines the quality of machined products and is influenced by
various cutting parameters. In machining operations, achieving
desired surface quality by optimization of machining parameters, is a
challenging job. In case of mating components the surface roughness
become more essential and is influenced by the cutting parameters,
because, these quality structures are highly correlated and are
expected to be influenced directly or indirectly by the direct effect of
process parameters or their interactive effects (i.e. on process
environment). In this work, the effects of selected process parameters
on surface roughness and subsequent setting of parameters with the
levels have been accomplished by Taguchi’s parameter design
approach. The experiments have been performed as per the
combination of levels of different process parameters suggested by
L9 orthogonal array. Experimental investigation of the end milling of
AISI D2 steel with carbide tool by varying feed, speed and depth of
cut and the surface roughness has been measured using surface
roughness tester. Analyses of variance have been performed for mean
and signal-to-noise ratio to estimate the contribution of the different
process parameters on the process.
Abstract: Biofuels production has come forth as a future
technology to combat the problem of depleting fossil fuels. Bio-based
ethanol production from enzymatic lignocellulosic biomass
degradation serves an efficient method and catching the eye of
scientific community. High cost of the enzyme is the major obstacle
in preventing the commercialization of this process. Thus main
objective of the present study was to optimize composition of
medium components for enhancing cellulase production by newly
isolated strain of Bacillus tequilensis. Nineteen factors were taken
into account using statistical Plackett-Burman Design. The significant
variables influencing the cellulose production were further employed
in statistical Response Surface Methodology using Central
Composite Design for maximizing cellulase production. The
optimum medium composition for cellulase production was: peptone
(4.94 g/L), ammonium chloride (4.99 g/L), yeast extract (2.00 g/L),
Tween-20 (0.53 g/L), calcium chloride (0.20 g/L) and cobalt chloride
(0.60 g/L) with pH 7, agitation speed 150 rpm and 72 h incubation at
37oC. Analysis of variance (ANOVA) revealed high coefficient of
determination (R2) of 0.99. Maximum cellulase productivity of 11.5
IU/ml was observed against the model predicted value of 13 IU/ml.
This was found to be optimally active at 60oC and pH 5.5.
Abstract: This study is concerned with the optimization of
fermentation parameters for the hyper production of mannanase from
Fusarium oxysporum SS-25 employing two step statistical strategy
and kinetic characterization of crude enzyme preparation. The
Plackett-Burman design used to screen out the important factors in
the culture medium revealed 20% (w/w) wheat bran, 2% (w/w) each
of potato peels, soyabean meal and malt extract, 1% tryptone, 0.14%
NH4SO4, 0.2% KH2PO4, 0.0002% ZnSO4, 0.0005% FeSO4, 0.01%
MnSO4, 0.012% SDS, 0.03% NH4Cl, 0.1% NaNO3 in brewer’s spent
grain based medium with 50% moisture content, inoculated with
2.8×107 spores and incubated at 30oC for 6 days to be the main
parameters influencing the enzyme production. Of these factors, four
variables including soyabean meal, FeSO4, MnSO4 and NaNO3 were
chosen to study the interactive effects and their optimum levels in
central composite design of response surface methodology with the
final mannanase yield of 193 IU/gds. The kinetic characterization
revealed the crude enzyme to be active over broader temperature and
pH range. This could result in 26.6% reduction in kappa number with
4.93% higher tear index and 1% increase in brightness when used to
treat the wheat straw based kraft pulp. The hydrolytic potential of
enzyme was also demonstrated on both locust bean gum and guar
gum.
Abstract: Brown seaweeds are abundant in Portuguese coastline
and represent an almost unexploited marine economic resource. One
of the most common species, easily available for harvesting in the
northwest coast, is Saccorhiza polyschides grows in the lowest shore
and costal rocky reefs. It is almost exclusively used by local farmers
as natural fertilizer, but contains a substantial amount of valuable
compounds, particularly alginates, natural biopolymers of high
interest for many industrial applications.
Alginates are natural polysaccharides present in cell walls of
brown seaweed, highly biocompatible, with particular properties that
make them of high interest for the food, biotechnology, cosmetics
and pharmaceutical industries. Conventional extraction processes are
based on thermal treatment. They are lengthy and consume high
amounts of energy and solvents. In recent years, microwave-assisted
extraction (MAE) has shown enormous potential to overcome major
drawbacks that outcome from conventional plant material extraction
(thermal and/or solvent based) techniques, being also successfully
applied to the extraction of agar, fucoidans and alginates. In the
present study, acid pretreatment of brown seaweed Saccorhiza
polyschides for subsequent microwave-assisted extraction (MAE) of
alginate was optimized. Seaweeds were collected in Northwest
Portuguese coastal waters of the Atlantic Ocean between May and
August, 2014. Experimental design was used to assess the effect of
temperature and acid pretreatment time in alginate extraction.
Response surface methodology allowed the determination of the
optimum MAE conditions: 40 mL of HCl 0.1 M per g of dried
seaweed with constant stirring at 20ºC during 14h. Optimal acid
pretreatment conditions have enhanced significantly MAE of
alginates from Saccorhiza polyschides, thus contributing for the
development of a viable, more environmental friendly alternative to
conventional processes.
Abstract: Enterprise Architecture (EA) is a strategy that is
employed by enterprises in order to align their business and
Information Technology (IT). EA is managed, developed, and
maintained through Enterprise Architecture Implementation
Methodology (EAIM). Effectiveness of EA implementation is the
degree in which EA helps to achieve the collective goals of the
organization. This paper analyzes the results of a survey that aims to
explore the factors that affect the effectiveness of EAIM and
specifically the relationship between factors and effectiveness of the
output and functionality of EA project. The exploratory factor
analysis highlights a specific set of five factors: alignment,
adaptiveness, support, binding, and innovation. The regression
analysis shows that there is a statistically significant and positive
relationship between each of the five factors and the effectiveness of
EAIM. Consistent with theory and practice, the most prominent
factor for developing an effective EAIM is innovation. The findings
contribute to the measuring the effectiveness of EA implementation
project by providing an indication of the measurement
implementation approaches which is used by the Enterprise
Architects, and developing an effective EAIM.
Abstract: Enterprise Architecture (EA) Implementation
Methodologies have become an important part of EA projects.
Several implementation methodologies have been proposed, as a
theoretical and practical approach, to facilitate and support the
development of EA within an enterprise. A significant question when
facing the starting of EA implementation is deciding which
methodology to utilize. In order to answer this question, a framework
with several criteria is applied in this paper for the comparative
analysis of existing EA implementation methodologies. Five EA
implementation methodologies including: EAP, TOGAF, DODAF,
Gartner, and FEA are selected in order to compare with proposed
framework. The results of the comparison indicate that those
methodologies have not reached a sufficient maturity as whole due to
lack of consideration on requirement management, maintenance,
continuum, and complexities in their process. The framework has
also ability for the evaluation of any kind of EA implementation
methodologies.
Abstract: Artificial Immune Systems (AIS), inspired by the
human immune system, are algorithms and mechanisms which are
self-adaptive and self-learning classifiers capable of recognizing and
classifying by learning, long-term memory and association. Unlike
other human system inspired techniques like genetic algorithms and
neural networks, AIS includes a range of algorithms modeling on
different immune mechanism of the body. In this paper, a mechanism
of a human immune system based on apoptosis is adopted to build an
Intrusion Detection System (IDS) to protect computer networks.
Features are selected from network traffic using Fisher Score. Based
on the selected features, the record/connection is classified as either
an attack or normal traffic by the proposed methodology. Simulation
results demonstrates that the proposed AIS based on apoptosis
performs better than existing AIS for intrusion detection.
Abstract: The aim of the present work was to statistically design
an autotrophic medium for maximum biomass production by
Chlorella pyrenoidosa using response surface methodology. After
evaluating one factor at a time approach, K2HPO4, KNO3,
MgSO4.7H2O and NaHCO3 were preferred over the other
components of the fog’s medium as most critical autotrophic medium
components. The study showed that the maximum biomass yield was
achieved while the concentrations of MgSO4.7H2O, K2HPO4, KNO3
and NaHCO3 were 0.409 g/L, 0.24 g/L, 1.033 g/L, and 3.265 g/L,
respectively. The study reported that the biomass productivity of C.
pyrenoidosa improved from 0.14 g/L in defined fog’s medium to 1.40
g/L in modified fog’s medium resulting 10 fold increase. The
biochemical composition biosynthesis of C. pyrenoidosa was altered
using nitrogen limiting stress bringing about 5.23 fold increase in
lipid content than control (cell without stress), as analyzed by FTIR
integration method.
Abstract: Supermarkets are the most electricity-intensive type of
commercial buildings. The unsuitable indoor environment of a
supermarket provided by abnormal HVAC operations incurs waste
energy consumption in refrigeration systems. This current study
briefly describes significantly solid backgrounds and proposes easyto-
use analysis terminology for investigating the impact of HVAC
operations on refrigeration power consumption using the field-test
data obtained from building automation system (BAS). With solid
backgrounds and prior knowledge, expected energy interactions
between HVAC and refrigeration systems are proposed through
Pearson’s correlation analysis (R value) by considering correlations
between equipment power consumption and dominantly independent
variables (driving force conditions).The R value can be conveniently
utilized to evaluate how strong relations between equipment
operations and driving force parameters are. The calculated R values
obtained from field data are compared to expected ranges of R values
computed by energy interaction methodology. The comparisons can
separate the operational conditions of equipment into faulty and
normal conditions. This analysis can simply investigate the condition
of equipment operations or building sensors because equipment could
be abnormal conditions due to routine operations or faulty
commissioning processes in field tests. With systematically solid and
easy-to-use backgrounds of interactions provided in the present
article, the procedures can be utilized as a tool to evaluate the proper
commissioning and routine operations of HVAC and refrigeration
systems to detect simple faults (e.g. sensors and driving force
environment of refrigeration systems and equipment set-point) and
optimize power consumption in supermarket buildings. Moreover,
the analysis will be used to further study the FDD research for
supermarkets in future.
Abstract: Nonstandard tests are necessary for analyses and
verification of new developed structural and technological solutions
with application of composite materials. One of the most critical
primary structural parts of a typical aerospace structure is T-joint.
This structural element is loaded mainly in shear, bending, peel and
tension. The paper is focused on the shear loading simulations. The
aim of the work is to obtain a representative uniform distribution of
shear loads along T-joint during the mechanical testing. A new
design of T-joint test procedure, numerical simulation and
optimization of representative boundary conditions are presented.
The different conditions and inaccuracies both in simulations and
experiments are discussed. The influence of different parameters on
stress and strain distributions is demonstrated on T-joint made of
CFRP (carbon fibre reinforced plastic). A special test rig designed by
VZLU (Aerospace Research and Test Establishment) for T-shear test
procedure is presented.
Abstract: Health analytics (HA) is used in healthcare systems
for effective decision making, management and planning of
healthcare and related activities. However, user resistances, unique
position of medical data content and structure (including
heterogeneous and unstructured data) and impromptu HA projects
have held up the progress in HA applications. Notably, the accuracy
of outcomes depends on the skills and the domain knowledge of the
data analyst working on the healthcare data. Success of HA depends
on having a sound process model, effective project management and
availability of supporting tools. Thus, to overcome these challenges
through an effective process model, we propose a HA process model
with features from rational unified process (RUP) model and agile
methodology.
Abstract: This paper aims at finding a suitable neural network
for monitoring congestion level in electrical power systems. In this
paper, the input data has been framed properly to meet the target
objective through supervised learning mechanism by defining normal
and abnormal operating conditions for the system under study. The
congestion level, expressed as line congestion index (LCI), is
evaluated for each operating condition and is presented to the NN
along with the bus voltages to represent the input and target data.
Once, the training goes successful, the NN learns how to deal with a
set of newly presented data through validation and testing
mechanism. The crux of the results presented in this paper rests on
performance comparison of a multi-layered feed forward neural
network with eleven types of back propagation techniques so as to
evolve the best training criteria. The proposed methodology has been
tested on the standard IEEE-14 bus test system with the support of
MATLAB based NN toolbox. The results presented in this paper
signify that the Levenberg-Marquardt backpropagation algorithm
gives best training performance of all the eleven cases considered in
this paper, thus validating the proposed methodology.