Abstract: This study was aimed to determine seasonal variations
of leaf nutrient concentrations to define nutrient needs related to
growing period and to compare irrigation programs in terms of
nutrient uptake. In this study,'Starkrimson Delicious' variety grafted
onto seedling rootstock was used during 2009-2010 growing seasons.
The study was conducted at E─ƒirdir Fruit Growing Research Station.
Leaf samples were taken in five different sample seasons (May, June,
July, August and September). Four different pan coefficients (0.50,
0.75, 1.0, 1.25) were applied during drip irrigation treatments in 7
days irrigation interval. Leaf K, Mg, Ca, P, Fe, Zn, Mn and Cu
concentrations were determined.
The results showed that among the seasonal changes, the highest
concentrations of K, Mg, P and Mn in leaves were recorded in May,
followed by a decrease in the other months, while in contrast Ca and
Fe showed the lowest concentration in May.
Results of the study demonstrate that among irrigation programs K
and Cu concentration in plants was significantly influenced. Cu
concentrations decreased with seasonal variations and different
irrigation programs. Thus, nutrient needs of 'Starkrimson Delicious'apple trees at different growth stages should be taken into
consideration before making effective fertilization program.
Abstract: Face recognition in the infrared spectrum has attracted a lot of interest in recent years. Many of the techniques used in infrared are based on their visible counterpart, especially linear techniques like PCA and LDA. In this work, we introduce a probabilistic Bayesian framework for face recognition in the infrared spectrum. In the infrared spectrum, variations can occur between face images of the same individual due to pose, metabolic, time changes, etc. Bayesian approaches permit to reduce intrapersonal variation, thus making them very interesting for infrared face recognition. This framework is compared with classical linear techniques. Non linear techniques we developed recently for infrared face recognition are also presented and compared to the Bayesian face recognition framework. A new approach for infrared face extraction based on SVM is introduced. Experimental results show that the Bayesian technique is promising and lead to interesting results in the infrared spectrum when a sufficient number of face images is used in an intrapersonal learning process.
Abstract: In aircraft applications, according to the nature of
electrical equipment its location may be in unpressurized area or very
close to the engine; thus, the environmental conditions may change
from atmospheric pressure to less than 100 mbar, and the temperature
may be higher than the ambient one as in most real working
conditions of electrical equipment. Then, the classical Paschen curve
has to be replotted since these parameters may affect the discharge
ignition voltage. In this paper, we firstly investigate the domain of
validity of two corrective expressions on the Paschen-s law found in
the literature, in case of changing the air environment and known as
Peek and Dunbar corrections. Results show that these corrections are
no longer valid for combined variation of temperature and pressure.
After that, a new empirical expression for breakdown voltage is
proposed and is validated in the case of combined variations of
temperature and pressure.
Abstract: A set of Artificial Neural Network (ANN) based methods
for the design of an effective system of speech recognition of
numerals of Assamese language captured under varied recording
conditions and moods is presented here. The work is related to
the formulation of several ANN models configured to use Linear
Predictive Code (LPC), Principal Component Analysis (PCA) and
other features to tackle mood and gender variations uttering numbers
as part of an Automatic Speech Recognition (ASR) system in
Assamese. The ANN models are designed using a combination of
Self Organizing Map (SOM) and Multi Layer Perceptron (MLP)
constituting a Learning Vector Quantization (LVQ) block trained in a
cooperative environment to handle male and female speech samples
of numerals of Assamese- a language spoken by a sizable population
in the North-Eastern part of India. The work provides a comparative
evaluation of several such combinations while subjected to handle
speech samples with gender based differences captured by a microphone
in four different conditions viz. noiseless, noise mixed, stressed
and stress-free.
Abstract: In this paper, a novel approach for robust trajectory tracking of induction motor drive is presented. By combining variable structure systems theory with fuzzy logic concept and neural network techniques, a new algorithm is developed. Fuzzy logic was used for the adaptation of the learning algorithm to improve the robustness of learning and operating of the neural network. The developed control algorithm is robust to parameter variations and external influences. It also assures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the designed controller of induction motor drives which considered as highly non linear dynamic complex systems and variable characteristics over the operating conditions.
Abstract: In this study we propose a novel monitor hydraulic
automatic gauge control (HAGC) system based on fuzzy feedforward
controller. This is used in the development of cold rolling
mill automation system to improve the quality of cold strip. According to features/ properties of entry steel strip like its average
yield stress, width of strip, and desired exit thickness, this controller realizes the compensation for the exit thickness error. The traditional methods of adjusting the roller position, can-t tolerate the variance in
the entry steel strip. The proposed method uses a mathematical model
of the system together with the expert knowledge to perform this adjustment while minimizing the effect of the stated problem. In
order to improve the speed of the controller in rejecting disturbances
introduced by entry strip thickness variations, expert knowledge is added as a feed-forward term to the HAGC system. Simulation
results for the application of the proposed controller to a real cold mill show that the exit strip quality is highly improved.
Abstract: In order to study seed yield and seed yield
components in bean under reduced irrigation condition and
assessment drought tolerance of genotypes, 15 lines of White beans
were evaluated in two separate RCB design with 3 replications under
stress and non stress conditions. Analysis of variance showed that
there were significant differences among varieties in terms of traits
under study, indicating the existence of genetic variation among
varieties. The results indicate that drought stress reduced seed yield,
number of seed per plant, biological yield and number of pod in
White been. In non stress condition, yield was highly correlated with
the biological yield, whereas in stress condition it was highly
correlated with harvest index. Results of stepwise regression showed
that, selection can we done based on, biological yield, harvest index,
number of seed per pod, seed length, 100 seed weight. Result of path
analysis showed that the highest direct effect, being positive, was
related to biological yield in non stress and to harvest index in stress
conditions. Factor analysis were accomplished in stress and nonstress
condition a, there were 4 factors that explained more than 76
percent of total variations. We used several selection indices such as
Stress Susceptibility Index ( SSI ), Geometric Mean Productivity (
GMP ), Mean Productivity ( MP ), Stress Tolerance Index ( STI ) and
Tolerance Index ( TOL ) to study drought tolerance of genotypes, we
found that the best Stress Index for selection tolerance genotypes
were STI, GMP and MP were the greatest correlations between these
Indices and seed yield under stress and non stress conditions. In
classification of genotypes base on phenotypic characteristics, using
cluster analysis ( UPGMA ), all allels classified in 5 separate groups
in stress and non stress conditions.
Abstract: The productivity of software development is one of the major concerns for project managers. Given the increasing complexity of the software being developed and the concomitant rise in the typical project size, the productivity has not consistently improved. By analyzing the latest release of ISBSG data repository with 4106 projects ever developed, we report on the factors found to significantly influence productivity, and present an original model for the estimation of productivity during project design. We further illustrate that software development productivity has experienced irregular variations between the years 1995 and 2005. Considering the factors significant to productivity, we found its variations are primarily caused by the variations of average team size for the development and the unbalanced use of the less productive development language 3GL.
Abstract: In this work, we treat the problems related to chemical and petrochemical plants of a certain complex process taking the centrifugal compressor as an example, a system being very complex by its physical structure as well as its behaviour (surge phenomenon). We propose to study the application possibilities of the recent control approaches to the compressor behaviour, and consequently evaluate their contribution in the practical and theoretical fields. Facing the studied industrial process complexity, we choose to make recourse to fuzzy logic for analysis and treatment of its control problem owing to the fact that these techniques constitute the only framework in which the types of imperfect knowledge can jointly be treated (uncertainties, inaccuracies, etc..) offering suitable tools to characterise them. In the particular case of the centrifugal compressor, these imperfections are interpreted by modelling errors, the neglected dynamics, no modelisable dynamics and the parametric variations. The purpose of this paper is to produce a total robust nonlinear controller design method to stabilize the compression process at its optimum steady state by manipulating the gas rate flow. In order to cope with both the parameter uncertainty and the structured non linearity of the plant, the proposed method consists of a linear steady state regulation that ensures robust optimal control and of a nonlinear compensation that achieves the exact input/output linearization.
Abstract: Culture and family structure provide a sense security.
Further, the chrono, macro and micro contexts of development
influence developmental transitions and timetable particularly owing
to variations in the macrosystem associated with non normative life
events like migration. Migration threatens family links, security and
attachment bonds. Rising migratory trends have prompted an
increased interest in migration consequences on familial bonds,
developmental autonomy, socialization process, and sense of
security. This paper takes a narrative approach and applies the
attachment paradigm from a lifespan perspective, to examine the
settlement experiences of an India-born migrant student in Sydney,
Australia. It focuses on her quest to preserve family ties; her remote
secure base; her continual struggle to balance dependency and
autonomy, a major developmental milestone. As positional parental
power is culturally more potent in the Indian society, the paper
therefore raises some important concerns related to cultural
expectations, adaptation, acculturative stress and sense of security.
Abstract: Threedimensional numerical simulations are conducted on a full scale CANDU Moderator and Transient variations of the temperature and velocity distributions inside the tank are determined. The results show that the flow and temperature distributions inside the moderator tank are three dimensional and no symmetry plane can be identified.Competition between the upward moving buoyancy driven flows and the downward moving momentum driven flows, results in the formation of circulation zones. The moderator tank operates in the buoyancy driven mode and any small disturbances in the flow or temperature makes the system unstable and asymmetric. Different types of temperature fluctuations are noted inside the tank: (i) large amplitude are at the boundaries between the hot and cold (ii) low amplitude are in the core of the tank (iii) high frequency fluctuations are in the regions with high velocities and (iv) low frequency fluctuations are in the regions with lower velocities.
Abstract: The experimental thermal performance of two heat
exchangers in closed-wet cooling tower (CWCT) was investigated in
this study. The test sections are heat exchangers which have multi path
that is used as the entrance of cooling water and are consisting of
bare-type copper tubes between 15.88mm and 19.05mm. The process
fluids are the cooling water that flows from top part of heat exchanger
to bottom side in the inner side of tube, and spray water that flows
gravitational direction in the outer side of it. Air contacts its outer side
of that as it counterflows. Heat and mass transfer coefficients and
cooling capacity were calculated with variations of process fluids,
multi path and different diameter tubes to figure out the performance
of characteristics of CWCT.
The main results were summarized as follows: The results show this
experiment is reliable with values of heat and mass transfer
coefficients comparing to values of correlations. Heat and mass
transfer coefficients and cooling capacity of two paths are higher than
these with one path using 15.88 and 19.05mm tubes. Cooling capacity
per unit volume with 15.88mm tube using one and two paths are
higher than 19.05mm tube due to increase of surface area per unit
volume.
Abstract: The interaction of tunneling or mining with
groundwater has become a very relevant problem not only due to the
need to guarantee the safety of workers and to assure the efficiency of
the tunnel drainage systems, but also to safeguard water resources
from impoverishment and pollution risk. Therefore it is very
important to forecast the drainage processes (i.e., the evaluation of
drained discharge and drawdown caused by the excavation). The aim
of this study was to know better the system and to quantify the flow
drained from the Fontane mines, located in Val Germanasca (Turin,
Italy). This allowed to understand the hydrogeological local changes
in time. The work has therefore been structured as follows: the
reconstruction of the conceptual model with the geological,
hydrogeological and geological-structural study; the calculation of
the tunnel inflows (through the use of structural methods) and the
comparison with the measured flow rates; the water balance at the
basin scale. In this way it was possible to understand what are the
relationships between rainfall, groundwater level variations and the
effect of the presence of tunnels as a means of draining water.
Subsequently, it the effects produced by the excavation of the mining
tunnels was quantified, through numerical modeling. In particular,
the modeling made it possible to observe the drawdown variation as a
function of number, excavation depth and different mines linings.
Abstract: This paper presents a controller design technique for
Synchronous Reluctance Motor to improve its dynamic performance
with fast response and high accuracy. The sliding mode control is the
most attractive and suitable method to use for this purpose, since it is
simple in design and for its insensitivity to parameter variations or
external disturbances. When this method implemented it yields fast
dynamic response without overshoot and a zero steady-state error.
The current loop control with decentralized sliding mode is presented
in this paper. The mathematical model for the synchronous machine,
the inverter and the controller is developed. The stability of the
sliding mode controller is analyzed. Simulation of synchronous
reluctance motor and the controller with PWM-inverter has been
curried out, using the SIMULINK software package of MATLAB.
Simulation results are presented to show the effectiveness of the
approach.
Abstract: This paper deals with the problem of thermal and
mechanical shocks, which rising during operation, mostly at
interrupted cut. Here will be solved their impact on the cutting edge
tool life, the impact of coating technology on resistance to shocks
and experimental determination of tool life in heating flame.
Resistance of removable cutting edges against thermal and
mechanical shock is an important indicator of quality as well as its
abrasion resistance. Breach of the edge or its crumble may occur due
to cyclic loading. We can observe it not only during the interrupted
cutting (milling, turning areas abandoned hole or slot), but also in
continuous cutting. This is due to the volatility of cutting force on
cutting. Frequency of the volatility in this case depends on the type
of rising chips (chip size element). For difficult-to-machine materials
such as austenitic steel particularly happened at higher cutting speeds
for the localization of plastic deformation in the shear plane and for
the inception of separate elements substantially continuous chips.
This leads to variations of cutting forces substantially greater than for
other types of steel.
Abstract: There have been many variations of technologies that helped educators in teaching & learning. From the past research it is evident that Information Technology significantly increases student participation and interactivity in the classrooms. This research started with a aim to find whether adoption of Wi-Fi environment by Malaysian Higher Educational Institutions (HEI) can benefit students and staff equally. The study was carried out in HEI-s of Klang Valley, Malaysia and the data is gathered through paper based surveys. A sample size of 237 units were randomly selected from 5 higher educational institutions in the Klang Valley using the Stratified Random sampling method and from the analysis of the data, it was found that the implementation of wireless technologies in HEIs have created lot of opportunities and also challenges.
Abstract: This paper is focused on issues of process modeling
and two model based control strategies of a fed-batch sugar
crystallization process applying the concept of artificial neural
networks (ANNs). The control objective is to force the operation into
following optimal supersaturation trajectory. It is achieved by
manipulating the feed flow rate of sugar liquor/syrup, considered as
the control input. The control task is rather challenging due to the
strong nonlinearity of the process dynamics and variations in the
crystallization kinetics. Two control alternatives are considered –
model predictive control (MPC) and feedback linearizing control
(FLC). Adequate ANN process models are first built as part of the
controller structures. MPC algorithm outperforms the FLC approach
with respect to satisfactory reference tracking and smooth control
action. However, the MPC is computationally much more involved
since it requires an online numerical optimization, while for the FLC
an analytical control solution was determined.
Abstract: Mostly the real life signals are time varying in nature. For proper characterization of such signals, time-frequency representation is required. The STFT (short-time Fourier transform) is a classical tool used for this purpose. The limitation of the STFT is its fixed time-frequency resolution. Thus, an enhanced version of the STFT, which is based on the cross-level sampling, is devised. It can adapt the sampling frequency and the window function length by following the input signal local variations. Therefore, it provides an adaptive resolution time-frequency representation of the input. The computational complexity of the proposed STFT is deduced and compared to the classical one. The results show a significant gain of the computational efficiency and hence of the processing power. The processing error of the proposed technique is also discussed.
Abstract: The predictability of masonry arch bridges and their
behaviour is widely considered doubtful due to the lack of knowledge
about the conditions of a given masonry arch bridge. The assessment
methods for masonry arch bridges are MEXE, ARCHIE, RING and
Frame Analysis Method. The material properties of the masonry and
fill material are extremely difficult to determine accurately.
Consequently, it is necessary to examine the effect of load dispersal
angle through the fill material, the effect of variations in the stiffness
of the masonry, the tensile strength of the masonry mortar continuum
and the compressive strength of the masonry mortar continuum. It is
also important to understand the effect of fill material on load
dispersal angle to determine their influence on ratings. In this paper a
series of parametric studies, to examine the sensitivity of assessment
ratings to the various sets of input data required by the frame analysis
method, are carried out.
Abstract: Dichotomization of the outcome by a single cut-off point is an important part of various medical studies. Usually the relationship between the resulted dichotomized dependent variable and explanatory variables is analyzed with linear regression, probit regression or logistic regression. However, in many real-life situations, a certain cut-off point dividing the outcome into two groups is unknown and can be specified only approximately, i.e. surrounded by some (small) uncertainty. It means that in order to have any practical meaning the regression model must be robust to this uncertainty. In this paper, we show that neither the beta in the linear regression model, nor its significance level is robust to the small variations in the dichotomization cut-off point. As an alternative robust approach to the problem of uncertain medical categories, we propose to use the linear regression model with the fuzzy membership function as a dependent variable. This fuzzy membership function denotes to what degree the value of the underlying (continuous) outcome falls below or above the dichotomization cut-off point. In the paper, we demonstrate that the linear regression model of the fuzzy dependent variable can be insensitive against the uncertainty in the cut-off point location. In the paper we present the modeling results from the real study of low hemoglobin levels in infants. We systematically test the robustness of the binomial regression model and the linear regression model with the fuzzy dependent variable by changing the boundary for the category Anemia and show that the behavior of the latter model persists over a quite wide interval.