Abstract: Tensile armour wires provide a flexible pipe's
resistance to longitudinal stresses. Flexible pipe manufacturers need
to know the effect of defects such as scratches and cracks, with
dimensions less than 0.2mm which is the limit of the current nondestructive
detection technology, on the fracture stress and fracture
strain of the wire for quality assurance purposes. Recent research
involving the determination of the fracture strength of cracked wires
employed laboratory testing and classical fracture mechanics
approach using non-standardised fracture mechanics specimens
because standard test specimens could not be manufactured from the
wires owing to their sizes. In this work, the effect of miniature
cracks on the fracture properties of tensile armour wires was
investigated using laboratory and finite element tensile testing
simulations with the phenomenological shear fracture model. The
investigation revealed that the presence of cracks shallower than
0.2mm is worse on the fracture strain of the wire.
Abstract: This paper presents a generalization kernel for gravitational
potential determination by harmonic splines. It was shown
in [10] that the gravitational potential can be approximated using a
kernel represented as a Newton integral over the real Earth body. On
the other side, the theory of geopotential approximation by harmonic
splines uses spherically oriented kernels. The purpose of this paper
is to show that in the spherical case both kernels have the same type
of representation, which leads us to conclusion that it is possible
to consider the kernel represented as a Newton integral over the real
Earth body as a kind of generalization of spherically harmonic kernels
to real geometries.
Abstract: A concern that researchers usually face in different
applications of Artificial Neural Network (ANN) is determination of
the size of effective domain in time series. In this paper, trial and
error method was used on groundwater depth time series to determine
the size of effective domain in the series in an observation well in
Union County, New Jersey, U.S. different domains of 20, 40, 60, 80,
100, and 120 preceding day were examined and the 80 days was
considered as effective length of the domain. Data sets in different
domains were fed to a Feed Forward Back Propagation ANN with
one hidden layer and the groundwater depths were forecasted. Root
Mean Square Error (RMSE) and the correlation factor (R2) of
estimated and observed groundwater depths for all domains were
determined. In general, groundwater depth forecast improved, as
evidenced by lower RMSEs and higher R2s, when the domain length
increased from 20 to 120. However, 80 days was selected as the
effective domain because the improvement was less than 1% beyond
that. Forecasted ground water depths utilizing measured daily data
(set #1) and data averaged over the effective domain (set #2) were
compared. It was postulated that more accurate nature of measured
daily data was the reason for a better forecast with lower RMSE
(0.1027 m compared to 0.255 m) in set #1. However, the size of input
data in this set was 80 times the size of input data in set #2; a factor
that may increase the computational effort unpredictably. It was
concluded that 80 daily data may be successfully utilized to lower the
size of input data sets considerably, while maintaining the effective
information in the data set.
Abstract: This paper presents a NDT by infrared thermography with excitation CO2 Laser, wavelength of 10.6 μm. This excitation is the controllable heating beam, confirmed by a preliminary test on a wooden plate 1.2 m x 0.9 m x 1 cm. As the first practice, this method is applied to detecting the defect in CFRP heated by the Laser 300 W during 40 s. Two samples 40 cm x 40 cm x 4.5 cm are prepared, one with defect, another one without defect. The laser beam passes through the lens of a deviation device, and heats the samples placed at a determinate position and area. As a result, the absence of adhesive can be detected. This method displays prominently its application as NDT with the composite materials. This work gives a good perspective to characterize the laser beam, which is very useful for the next detection campaigns.
Abstract: Although backpropagation ANNs generally predict
better than decision trees do for pattern classification problems, they
are often regarded as black boxes, i.e., their predictions cannot be
explained as those of decision trees. In many applications, it is
desirable to extract knowledge from trained ANNs for the users to
gain a better understanding of how the networks solve the problems.
A new rule extraction algorithm, called rule extraction from artificial
neural networks (REANN) is proposed and implemented to extract
symbolic rules from ANNs. A standard three-layer feedforward ANN
is the basis of the algorithm. A four-phase training algorithm is
proposed for backpropagation learning. Explicitness of the extracted
rules is supported by comparing them to the symbolic rules generated
by other methods. Extracted rules are comparable with other methods
in terms of number of rules, average number of conditions for a rule,
and predictive accuracy. Extensive experimental studies on several
benchmarks classification problems, such as breast cancer, iris,
diabetes, and season classification problems, demonstrate the
effectiveness of the proposed approach with good generalization
ability.
Abstract: In this paper we discuss the problems of the long-term management policy of Lake Peipsi and the roles of natural and anthropogenic factors in the ecological state of the lake. The reduction of the pollution during the last 15 years could not give significant changes of the chemical composition of the water, what implicates the essential role that natural factors have on the ecological state of lake. One of the most important factors having impact on the hydrochemical cycles and ecological state is the hydrological regime which is clearly expressed in L. Peipsi. The absence on clear interrelations of climate cycles and nutrients suggest that complex abiotic and biotic interactions, which take place in the lake ecosystem, plays a significant role in the matter circulation mechanism within lake.
Abstract: The removal of hydrogen sulphide is required for reasons of health, odour problems, safety and corrosivity problems. The means of removing hydrogen sulphide mainly depend on its concentration and kind of medium to be purified. The paper deals with a method of hydrogen sulphide removal from the air by its catalytic oxidation to elemental sulphur with the use of Fe-EDTA complex. The possibility of obtaining fibrous filtering materials able to remove small concentrations of H2S from the air were described. The base of these materials is fibrous ion exchanger with Fe(III)- EDTA complex immobilized on their functional groups. The complex of trivalent iron converts hydrogen sulphide to elemental sulphur. Bivalent iron formed in the reaction is oxidized by the atmospheric oxygen, so complex of trivalent iron is continuously regenerated and the overall process can be accounted as pseudocatalytic. In the present paper properties of several fibrous catalysts based on ion exchangers with different chemical nature (weak acid,weak base and strong base) were described. It was shown that the main parameters affecting the process of catalytic oxidation are:concentration of hydrogen sulphide in the air, relative humidity of the purified air, the process time and the content of Fe-EDTA complex in the fibres. The data presented show that the filtering layers with anion exchange package are much more active in the catalytic processes of hydrogen sulphide removal than cation exchanger and inert materials. In the addition to the nature of the fibres relative air humidity is a critical factor determining efficiency of the material in the air purification from H2S. It was proved that the most promising carrier of the Fe-EDTA catalyst for hydrogen sulphide oxidation are Fiban A-6 and Fiban AK-22 fibres.
Abstract: During the last couple of years, the degree of dependence on IT systems has reached a dimension nobody imagined to be possible 10 years ago. The increased usage of mobile devices (e.g., smart phones), wireless sensor networks and embedded devices (Internet of Things) are only some examples of the dependency of modern societies on cyber space. At the same time, the complexity of IT applications, e.g., because of the increasing use of cloud computing, is rising continuously. Along with this, the threats to IT security have increased both quantitatively and qualitatively, as recent examples like STUXNET or the supposed cyber attack on Illinois water system are proofing impressively. Once isolated control systems are nowadays often publicly available - a fact that has never been intended by the developers. Threats to IT systems don’t care about areas of responsibility. Especially with regard to Cyber Warfare, IT threats are no longer limited to company or industry boundaries, administrative jurisdictions or state boundaries. One of the important countermeasures is increased cooperation among the participants especially in the field of Cyber Defence. Besides political and legal challenges, there are technical ones as well. A better, at least partially automated exchange of information is essential to (i) enable sophisticated situational awareness and to (ii) counter the attacker in a coordinated way. Therefore, this publication performs an evaluation of state of the art Intrusion Detection Message Exchange protocols in order to guarantee a secure information exchange between different entities.
Abstract: Achievement motivation is believed to promote
giftedness attracting people to invest in many programs to adopt
gifted students providing them with challenging activities.
Intellectual giftedness is founded on the fluid intelligence and
extends to more specific abilities through the growth and inputs from
the achievement motivation. Acknowledging the roles played by the
motivation in the development of giftedness leads to an effective
nurturing of gifted individuals. However, no study has investigated
the direct and indirect effects of the achievement motivation and
fluid intelligence on intellectual giftedness. Thus, this study
investigated the contribution of motivation factors to giftedness
development by conducting tests of fluid intelligence using Cattell
Culture Fair Test (CCFT) and analytical abilities using culture
reduced test items covering problem solving, pattern recognition,
audio-logic, audio-matrices, and artificial language, and self report
questionnaire for the motivational factors. A number of 180 highscoring
students were selected using CCFT from a leading university
in Malaysia. Structural equation modeling was employed using Amos
V.16 to determine the direct and indirect effects of achievement
motivation factors (self confidence, success, perseverance,
competition, autonomy, responsibility, ambition, and locus of
control) on the intellectual giftedness. The findings showed that the
hypothesized model fitted the data, supporting the model postulates
and showed significant and strong direct and indirect effects of the
motivation and fluid intelligence on the intellectual giftedness.
Abstract: In this paper, the application of neural networks to study the design of short-term temperature forecasting (STTF) Systems for Kermanshah city, west of Iran was explored. One important architecture of neural networks named Multi-Layer Perceptron (MLP) to model STTF systems is used. Our study based on MLP was trained and tested using ten years (1996-2006) meteorological data. The results show that MLP network has the minimum forecasting error and can be considered as a good method to model the STTF systems.
Abstract: The use of radar in Quantitative Precipitation Estimation (QPE) for radar-rainfall measurement is significantly beneficial. Radar has advantages in terms of high spatial and temporal condition in rainfall measurement and also forecasting. In Malaysia, radar application in QPE is still new and needs to be explored. This paper focuses on the Z/R derivation works of radarrainfall estimation based on rainfall classification. The works developed new Z/R relationships for Klang River Basin in Selangor area for three different general classes of rain events, namely low (10mm/hr, 30mm/hr) and also on more specific rain types during monsoon seasons. Looking at the high potential of Doppler radar in QPE, the newly formulated Z/R equations will be useful in improving the measurement of rainfall for any hydrological application, especially for flood forecasting.
Abstract: Increasing energy absorption is a significant parameter
in vehicle design. Absorbing more energy results in decreasing
occupant damage. Limitation of the deflection in a side impact results
in decreased energy absorption (SEA) and increased peak load (PL).
Hence a high crash force jeopardizes passenger safety and vehicle
integrity. The aims of this paper are to determine suitable dimensions
and material of a square beam subjected to side impact, in order to
maximize SEA and minimize PL. To achieve this novel goal, the
geometric parameters of a square beam are optimized using the
response surface method (RSM).multi-objective optimization is
performed, and the optimum design for different response features is
obtained.
Abstract: This study investigated a strategy of blending lead-laden sludge and Al-rich precursors to reduce the release of metals from the stabilized products. Using PbO as the simulated lead-laden sludge to sinter with γ-Al2O3 by Pb:Al molar ratios of 1:2 and 1:12, PbAl2O4 and PbAl12O19 were formed as final products during the sintering process, respectively. By firing the PbO + γ-Al2O3 mixtures with different Pb/Al molar ratios at 600 to 1000 °C, the lead transformation was determined through X-ray diffraction (XRD) data. In Pb/Al molar ratio of 1/2 system, the formation of PbAl2O4 is initiated at 700 °C, but an effective formation was observed above 750 °C. An intermediate phase, Pb9Al8O21, was detected in the temperature range of 800-900 °C. However, different incorporation behavior for sintering PbO with Al-rich precursors at a Pb/Al molar ratio of 1/12 was observed during the formation of PbAl12O19 in this system. In the sintering process, both temperature and time effect on the formation of PbAl2O4 and PbAl12O19 phases were estimated. Finally, a prolonged leaching test modified from the U.S. Environmental Protection Agency-s toxicity characteristic leaching procedure (TCLP) was used to evaluate the durability of PbO, Pb9Al8O21, PbAl2O4 and PbAl12O19 phases. Comparison for the leaching results of the four phases demonstrated the higher intrinsic resistance of PbAl12O19 against acid attack.
Abstract: In the present study Schwertmannite (an iron oxide
hydroxide) is selected as an adsorbent for defluoridation of water.
The adsorbent was prepared by wet chemical process and was
characterized by SEM, XRD and BET. The fluoride adsorption
efficiency of the prepared adsorbent was determined with respect to
contact time, initial fluoride concentration, adsorbent dose and pH of
the solution. The batch adsorption data revealed that the fluoride
adsorption efficiency was highly influenced by the studied factors.
Equilibrium was attained within one hour of contact time indicating
fast kinetics and the adsorption data followed pseudo second order
kinetic model. Equilibrium isotherm data fitted to both Langmuir and
Freundlich isotherm models for a concentration range of 5-30 mg/L.
The adsorption system followed Langmuir isotherm model with
maximum adsorption capacity of 11.3 mg/g. The high adsorption
capacity of Schwertmannite points towards the potential of this
adsorbent for fluoride removal from aqueous medium.
Abstract: The purpose of the study is to determine the primary mathematics student teachers- views related to use instructional technology tools in course of the learning process and to reveal how the sample presentations towards different mathematical concepts affect their views. This is a qualitative study involving twelve mathematics students from a public university. The data gathered from two semi-structural interviews. The first one was realized in the beginning of the study. After that the representations prepared by the researchers were showed to the participants. These representations contain animations, Geometer-s Sketchpad activities, video-clips, spreadsheets, and power-point presentations. The last interview was realized at the end of these representations. The data from the interviews and content analyses were transcribed and read and reread to explore the major themes. Findings revealed that the views of the students changed in this process and they believed that the instructional technology tools should be used in their classroom.
Abstract: Injection forging is a Nett-shape manufacturing
process in which one or two punches move axially causing a radial
flow into a die cavity in a form which is prescribed by the exitgeometry,
such as pulley, flanges, gears and splines on a shaft. This
paper presents an experimental and numerical study of the injection
forging of splines in terms of load requirement and material flow.
Three dimensional finite element analyses are used to investigate the
effect of some important parameters in this process. The experiment
has been carried out using solid commercial lead billets with two
different billet diameters and four different dies.
Abstract: Road signs are the elements of roads with a lot of
influence in driver-s behavior. So that signals can fulfill its function,
they must overcome visibility and durability requirements,
particularly needed at night, when the coefficient of retroreflection
becomes a decisive factor in ensuring road safety. Accepting that the
visibility of the signage has implications for people-s safety, we
understand the importance to fulfill its function: to foster the highest
standards of service and safety in drivers. The usual conditions of
perception of any sign are determined by: age of the driver, reflective
material, luminosity, vehicle speed and emplacement. In this way,
this paper evaluates the different signals to increase the safety road.
Abstract: One of the most important requirements for the
operation and planning activities of an electrical utility is the
prediction of load for the next hour to several days out, known as
short term load forecasting. This paper presents the development of
an artificial neural network based short-term load forecasting model.
The model can forecast daily load profiles with a load time of one
day for next 24 hours. In this method can divide days of year with
using average temperature. Groups make according linearity rate of
curve. Ultimate forecast for each group obtain with considering
weekday and weekend. This paper investigates effects of temperature
and humidity on consuming curve. For forecasting load curve of
holidays at first forecast pick and valley and then the neural network
forecast is re-shaped with the new data. The ANN-based load models
are trained using hourly historical. Load data and daily historical
max/min temperature and humidity data. The results of testing the
system on data from Yazd utility are reported.
Abstract: This paper presents the applicability of artificial
neural networks for 24 hour ahead solar power generation forecasting
of a 20 kW photovoltaic system, the developed forecasting is suitable
for a reliable Microgrid energy management. In total four neural
networks were proposed, namely: multi-layred perceptron, radial
basis function, recurrent and a neural network ensemble consisting in
ensemble of bagged networks. Forecasting reliability of the proposed
neural networks was carried out in terms forecasting error
performance basing on statistical and graphical methods. The
experimental results showed that all the proposed networks achieved
an acceptable forecasting accuracy. In term of comparison the neural
network ensemble gives the highest precision forecasting comparing
to the conventional networks. In fact, each network of the ensemble
over-fits to some extent and leads to a diversity which enhances the
noise tolerance and the forecasting generalization performance
comparing to the conventional networks.
Abstract: This paper fist examines three set of bivariate cointegrations between any two of current accounts, stock markets, and currency exchange markets in ten Asian countries. Furthermore, we examined the effect of country characters on this bivariate cointegration. Our findings suggest that for three sets of cointegration test, each sample country at least exists one cointegration. India consistently exhibited a bi-directional causal relationship between any two of three indicators. Unlike Pan et al. (2007) and Phylaktis and Ravazzolo (2005), we found that such cointegration is influenced by three characteristics: capital control; flexibility in foreign exchange rates; and the ratio of trade to GDP. These characteristics are the result of liberalization in each Asian country. This implies that liberalization policies are effective on improving the cointegration between any two of financial markets and current account for ten Asian countries.