Abstract: Problems insulation of building structures is often
closely connected with the problem of moisture remediation. In the
case of historic buildings or if only part of the redevelopment of
envelope of structures, it is not possible to apply the classical external
thermal insulation composite systems. This application is mostly
effective thermal insulation plasters with high porosity and controlled
capillary properties which assures improvement of thermal properties
construction, its diffusion openness towards the external environment
and suitable treatment capillary properties of preventing the
penetration of liquid moisture and salts thereof toward the outer
surface of the structure.
With respect to the current trend of reducing the energy
consumption of building structures and reduce the production of CO2
is necessary to develop capillary-active materials characterized by
their low density, low thermal conductivity while maintaining good
mechanical properties. The aim of researchers at the Faculty of Civil
Engineering, Brno University of Technology is the development and
study of hygrothermal behaviour of optimal materials for thermal
insulation and rehabilitation of building structures with the possible
use of alternative, less energy demanding binders in comparison with
conventional, frequently used binder, which represents cement.
The paper describes the evaluation of research activities aimed at
the development of thermal insulation and repair materials using
lightweight aggregate and alternative binders such as metakaolin and
finely ground fly ash.
Abstract: This study was conducted Razakı grape variety (Vitis
vinifera L.) and its vine which was aged 19 was grown on 5 BB
rootstock in a vegetation period of 2014 in Afyon province in Turkey.
In this research, it was investigated whether the applications of
Control (C), 1/3 Cluster Tip Reduction (1/3 CTR), Shoot Tip
Reduction (STR), 1/3 CTR + STR, Boric Acid (BA), 1/3 CTR + BA,
STR + BA, 1/3 CTR + STR + BA on yield and yield components of
Razakı grape variety. The results were obtained as the highest fresh
grape yield (7.74 kg/vine) with C application; as the highest cluster
weight (244.62 g) with STR application; as the highest 100 berry
weight (504.08 g) with C application; as the highest maturity index
(36.89) with BA application; as the highest must yield (695.00 ml)
with BA and (695.00 ml) with 1/3 CTR + STR + BA applications; as
the highest intensity of L* color (46.93) with STR and (46.10) with
1/3 CTR + STR + BA applications; as the highest intensity of a*
color (-5.37) with 1/3 CTR + STR and (-5.01) with STR, as the
highest intensity of b* color (12.59) with STR application. The shoot
tip reduction to increase cluster weight and boric acid application to
increase maturity index of Razakı grape variety can be recommended.
Abstract: The introduction of degradable plastic materials into
agricultural sectors has represented a promising alternative to
promote green agriculture and environmental friendly of modern
farming practices. Major challenges of developing degradable
agricultural films are to identify the most feasible types of
degradation mechanisms, composition of degradable polymers and
related processing techniques. The incorrect choice of degradable
mechanisms to be applied during the degradation process will cause
premature losses of mechanical performance and strength. In order to
achieve controlled process of agricultural film degradation, the
compositions of degradable agricultural film also important in order
to stimulate degradation reaction at required interval of time and to
achieve sustainability of the modern agricultural practices. A set of
photodegradable polyethylene based agricultural film was developed
and produced, following the selective optimization of processing
parameters of the agricultural film manufacturing system. Example of
agricultural films application for oil palm seedlings cultivation is
presented.
Abstract: Phelipanche ramosa is the most damaging obligate
flowering parasitic weed on wide species of cultivated plants. The
semi-arid regions of the world are considered the main centers of this
parasitic plant that causes heavy infestation. This is due to its
production of high numbers of seeds (up to 200,000) that remain
viable for extended periods (up to 20 years). In this study, 13
treatments for the control of Phelipanche were carried out, which
included agronomic, chemical, and biological treatments and the use
of resistant plant methods. In 2014, a trial was performed at the
Department of Agriculture, Food and Environment, University of
Foggia (southern Italy), on processing tomato (cv ‘Docet’) grown in
pots filled with soil taken from a field that was heavily infested by P.
ramosa). The tomato seedlings were transplanted on May 8, 2014,
into a sandy-clay soil (USDA). A randomized block design with 3
replicates (pots) was adopted. During the growing cycle of the
tomato, at 70, 75, 81 and 88 days after transplantation, the number of
P. ramosa shoots emerged in each pot was determined. The tomato
fruit were harvested on August 8, 2014, and the quantitative and
qualitative parameters were determined. All of the data were
subjected to analysis of variance (ANOVA) using the JMP software
(SAS Institute Inc. Cary, NC, USA), and for comparisons of means
(Tukey's tests). The data show that each treatment studied did not
provide complete control against P. ramosa. However, the virulence
of the attacks was mitigated by some of the treatments tried: radicon
biostimulant, compost activated with Fusarium, mineral fertilizer
nitrogen, sulfur, enzone, and the resistant tomato genotype. It is
assumed that these effects can be improved by combining some of
these treatments with each other, especially for a gradual and
continuing reduction of the “seed bank” of the parasite in the soil.
Abstract: The paper deals with possibilities of interpretation of
iron ore reducibility tests. It presents a mathematical model
developed at Centre ENET, VŠB – Technical University of Ostrava,
Czech Republic for an evaluation of metallurgical material of blast
furnace feedstock such as iron ore, sinter or pellets. According to the
data from the test, the model predicts its usage in blast furnace
technology and its effects on production parameters of shaft
aggregate. At the beginning, the paper sums up the general concept
and experience in mathematical modelling of iron ore reduction. It
presents basic equation for the calculation and the main parts of the
developed model. In the experimental part, there is an example of
usage of the mathematical model. The paper describes the usage of
data for some predictive calculation. There are presented material,
method of carried test of iron ore reducibility. Then there are
graphically interpreted effects of used material on carbon
consumption, rate of direct reduction and the whole reduction
process.
Abstract: The problem of toughening in brittle materials
reinforced by fibers is complex, involving all of the mechanical
properties of fibers, matrix and the fiber/matrix interface, as well as
the geometry of the fiber. Development of new numerical methods
appropriate to toughening simulation and analysis is necessary. In
this work, we have performed simulations and analysis of toughening
in brittle matrix reinforced by randomly distributed fibers by means
of the discrete elements method. At first, we put forward a
mechanical model of toughening contributed by random fibers. Then
with a numerical program, we investigated the stress, damage and
bridging force in the composite material when a crack appeared in the
brittle matrix. From the results obtained, we conclude that: (i) fibers
of high strength and low elasticity modulus are beneficial to
toughening; (ii) fibers of relatively high elastic modulus compared to
the matrix may result in substantial matrix damage due to spalling
effect; (iii) employment of high-strength synthetic fibers is a good
option for toughening. We expect that the combination of the discrete
element method (DEM) with the finite element method (FEM) can
increase the versatility and efficiency of the software developed. The
present work can guide the design of ceramic composites of high
performance through the optimization of the parameters.
Abstract: In this paper, the problem of steady laminar boundary
layer flow and heat transfer over a permeable exponentially
stretching/shrinking sheet with generalized slip velocity is
considered. The similarity transformations are used to transform the
governing nonlinear partial differential equations to a system of
nonlinear ordinary differential equations. The transformed equations
are then solved numerically using the bvp4c function in MATLAB.
Dual solutions are found for a certain range of the suction and
stretching/shrinking parameters. The effects of the suction parameter,
stretching/shrinking parameter, velocity slip parameter, critical shear
rate and Prandtl number on the skin friction and heat transfer
coefficients as well as the velocity and temperature profiles are
presented and discussed.
Abstract: Long Distance Truck Drivers (LDTDs) have been
found to be a high risk group in the spread of HIV/AIDS globally;
perhaps, due to their high Sexual Risk Behaviours (SRBs).
Interventions for reducing SRBs in trucking population have not been
fully exploited. A quasi-experimental control group pretest-posttest
design was used to assess the efficacy of psycho-education and
behavioural skills training in reducing SRBs among LDTDs. Sixteen
drivers rivers were randomly assigned into either experimental or
control groups using balloting technique. Questionnaire was used as
an instrument for data collection. Repeated measures t-test and
independent t-test were used to test hypotheses. Intervention had
significant effect on the SRBs among LDTDs at post-test (t{7}=
6.01, p
Abstract: For optimal unbiased filter as mean-square and in the
case of functioning anomalous noises in the observation memory
channel, we have proved insensitivity of filter to inaccurate
knowledge of the anomalous noise intensity matrix and its
equivalence to truncated filter plotted only by non anomalous
components of an observation vector.
Abstract: Co-crystal is believed to improve the solubility and
dissolution rates and thus, enhanced the bioavailability of poor water
soluble drugs particularly during the oral route of administration.
With the existing of poorly soluble drugs in pharmaceutical industry,
the screening of co-crystal formation using carbamazepine (CBZ) as
a model drug compound with dicarboxylic acids co-crystal formers
(CCF) namely fumaric (FA) and succinic (SA) acids in ethanol has
been studied. The co-crystal formations were studied by varying the
mol ratio values of CCF to CBZ to access the effect of CCF
concentration on the formation of the co-crystal. Solvent evaporation,
slurry and cooling crystallization which representing the solution
based method co-crystal screening were used. Based on the
differential scanning calorimetry (DSC) analysis, the melting point of
CBZ-SA in different ratio was in the range between 188oC-189oC.
For CBZ-FA form A and CBZ-FA form B the melting point in
different ratio were in the range of 174oC-175oC and 185oC-186oC
respectively. The product crystal from the screening was also
characterized using X-ray powder diffraction (XRPD). The XRPD
pattern profile analysis has shown that the CBZ co-crystals with FA
and SA were successfully formed for all ratios studied. The findings
revealed that CBZ-FA co-crystal were formed in two different
polymorphs. It was found that CBZ-FA form A and form B were
formed from evaporation and slurry crystallization methods
respectively. On the other hand, in cooling crystallization method,
CBZ-FA form A was formed at lower mol ratio of CCF to CBZ and
vice versa. This study disclosed that different methods and mol ratios
during the co-crystal screening can affect the outcome of co-crystal
produced such as polymorphic forms of co-crystal and thereof. Thus,
it was suggested that careful attentions is needed during the screening
since the co-crystal formation is currently one of the promising
approach to be considered in research and development for
pharmaceutical industry to improve the poorly soluble drugs.
Abstract: The convective heat and mass transfer in nanofluid
flow through a porous media due to a permeable stretching sheet with
magnetic field, viscous dissipation, chemical reaction and Soret
effects are numerically investigated. Two types of nanofluids, namely
Cu-water and Ag-water were studied. The governing boundary layer
equations are formulated and reduced to a set of ordinary differential
equations using similarity transformations and then solved
numerically using the Keller box method. Numerical results are
obtained for the skin friction coefficient, Nusselt number and
Sherwood number as well as for the velocity, temperature and
concentration profiles for selected values of the governing
parameters. Excellent validation of the present numerical results has
been achieved with the earlier linearly stretching sheet problems in
the literature.
Abstract: Incineration of municipal solid waste (MSW) is one of
the key scopes in the global clean energy strategy. A computational
fluid dynamics (CFD) model was established in order to reveal these
features of the combustion process in a fixed porous bed of MSW.
Transporting equations and process rate equations of the waste bed
were modeled and set up to describe the incineration process,
according to the local thermal conditions and waste property
characters. Gas phase turbulence was modeled using k-ε turbulent
model and the particle phase was modeled using the kinetic theory of
granular flow. The heterogeneous reaction rates were determined
using Arrhenius eddy dissipation and the Arrhenius-diffusion
reaction rates. The effects of primary air flow rate and temperature in
the burning process of simulated MSW are investigated
experimentally and numerically. The simulation results in bed are
accordant with experimental data well. The model provides detailed
information on burning processes in the fixed bed, which is otherwise
very difficult to obtain by conventional experimental techniques.
Abstract: A model was constructed to predict the amount of
solar radiation that will make contact with the surface of the earth in
a given location an hour into the future. This project was supported
by the Southern Company to determine at what specific times during
a given day of the year solar panels could be relied upon to produce
energy in sufficient quantities. Due to their ability as universal
function approximators, an artificial neural network was used to
estimate the nonlinear pattern of solar radiation, which utilized
measurements of weather conditions collected at the Griffin, Georgia
weather station as inputs. A number of network configurations and
training strategies were utilized, though a multilayer perceptron with
a variety of hidden nodes trained with the resilient propagation
algorithm consistently yielded the most accurate predictions. In
addition, a modeled direct normal irradiance field and adjacent
weather station data were used to bolster prediction accuracy. In later
trials, the solar radiation field was preprocessed with a discrete
wavelet transform with the aim of removing noise from the
measurements. The current model provides predictions of solar
radiation with a mean square error of 0.0042, though ongoing efforts
are being made to further improve the model’s accuracy.
Abstract: In this paper, a direct power control (DPC)
strategies have been investigated in order to control a high
power AC/DC converter with time variable load. This converter
is composed of a three level three phase neutral point clamped
(NPC) converter as rectifier and an H-bridge four quadrant
current control converter. In the high power application,
controller not only must adjust the desire outputs but also
decrease the level of distortions which are injected to the network
from the converter. Regarding to this reason and nonlinearity
of the power electronic converter, the conventional controllers
cannot achieve appropriate responses. In this research, the
precise mathematical analysis has been employed to design the
appropriate controller in order to control the time variable
load. A DPC controller has been proposed and simulated using
Matlab/ Simulink. In order to verify the simulation result, a real
time simulator- OPAL-RT- has been employed. In this paper,
the dynamic response and stability of the high power NPC
with variable load has been investigated and compared with
conventional types using a real time simulator. The results proved
that the DPC controller is more stable and has more precise
outputs in comparison with conventional controller.
Abstract: In this study, a computational fluid dynamics (CFD)
model has been developed for studying the effect of surface
roughness profile on the EHL problem. The cylinders contact
geometry, meshing and calculation of the conservation of mass and
momentum equations are carried out using the commercial software
packages ICEMCFD and ANSYS Fluent. The user defined functions
(UDFs) for density, viscosity and elastic deformation of the cylinders
as the functions of pressure and temperature are defined for the CFD
model. Three different surface roughness profiles are created and
incorporated into the CFD model. It is found that the developed CFD
model can predict the characteristics of fluid flow and heat transfer in
the EHL problem, including the main parameters such as pressure
distribution, minimal film thickness, viscosity, and density changes.
The results obtained show that the pressure profile at the center of the
contact area directly relates to the roughness amplitude. A rough
surface with kurtosis value of more than 3 has greater influence over
the fluctuated shape of pressure distribution than in other cases.
Abstract: Traditional document representation for classification
follows Bag of Words (BoW) approach to represent the term weights.
The conventional method uses the Vector Space Model (VSM) to
exploit the statistical information of terms in the documents and they
fail to address the semantic information as well as order of the terms
present in the documents. Although, the phrase based approach
follows the order of the terms present in the documents rather than
semantics behind the word. Therefore, a semantic concept based
approach is used in this paper for enhancing the semantics by
incorporating the ontology information. In this paper a novel method
is proposed to forecast the intraday stock market price directional
movement based on the sentiments from Twitter and money control
news articles. The stock market forecasting is a very difficult and
highly complicated task because it is affected by many factors such
as economic conditions, political events and investor’s sentiment etc.
The stock market series are generally dynamic, nonparametric, noisy
and chaotic by nature. The sentiment analysis along with wisdom of
crowds can automatically compute the collective intelligence of
future performance in many areas like stock market, box office sales
and election outcomes. The proposed method utilizes collective
sentiments for stock market to predict the stock price directional
movements. The collective sentiments in the above social media have
powerful prediction on the stock price directional movements as
up/down by using Granger Causality test.
Abstract: The arm length, hand length, hand breadth and middle
finger length of 1540 right-handed industrial workers of Haryana
state was used to assess the relationship between the upper limb
dimensions and stature. Initially, the data were analyzed using basic
univariate analysis and independent t-tests; then simple and multiple
linear regression models were used to estimate stature using SPSS
(version 17). There was a positive correlation between upper limb
measurements (hand length, hand breadth, arm length and middle
finger length) and stature (p < 0.01), which was highest for hand
length. The accuracy of stature prediction ranged from ± 54.897 mm
to ± 58.307 mm. The use of multiple regression equations gave better
results than simple regression equations. This study provides new
forensic standards for stature estimation from the upper limb
measurements of male industrial workers of Haryana (India). The
results of this research indicate that stature can be determined using
hand dimensions with accuracy, when only upper limb is available
due to any reasons likewise explosions, train/plane crashes, mutilated
bodies, etc. The regression formula derived in this study will be
useful for anatomists, archaeologists, anthropologists, design
engineers and forensic scientists for fairly prediction of stature using
regression equations.
Abstract: These days customer satisfaction plays vital role in
any business. When customer searches for a product, significantly a
junk of irrelevant information is what is given, leading to customer
dissatisfaction. To provide exactly relevant information on the
searched product, we are proposing a model of KaaS (Knowledge as
a Service), which pre-processes the information using decision
making paradigm using Multi-agents.
Information obtained from various sources is taken to derive
knowledge and they are linked to Cloud to capture new idea. The
main focus of this work is to acquire relevant information
(knowledge) related to product, then convert this knowledge into a
service for customer satisfaction and deploy on cloud.
For achieving these objectives we are have opted to use multi
agents. They are communicating and interacting with each other,
manipulate information, provide knowledge, to take decisions. The
paper discusses about KaaS as an intelligent approach for Knowledge
acquisition.
Abstract: The aim of software maintenance is to maintain
the software system in accordance with advancement in software
and hardware technology. One of the early works on software
maintenance is to extract information at higher level of abstraction. In
this paper, we present the process of how to design an information
extraction tool for software maintenance. The tool can extract the
basic information from old programs such as about variables, based
classes, derived classes, objects of classes, and functions. The tool
have two main parts; the lexical analyzer module that can read the
input file character by character, and the searching module which
users can get the basic information from the existing programs. We
implemented this tool for a patterned sub-C++ language as an input
file.
Abstract: An artificial neural network is a mathematical model
inspired by biological neural networks. There are several kinds of
neural networks and they are widely used in many areas, such as:
prediction, detection, and classification. Meanwhile, in day to day life,
people always have to make many difficult decisions. For example,
the coach of a soccer club has to decide which offensive player
to be selected to play in a certain game. This work describes a
novel Neural Network using a combination of the General Regression
Neural Network and the Probabilistic Neural Networks to help a
soccer coach make an informed decision.