Abstract: This paper is devoted to a delayed periodic predatorprey system with non-monotonic numerical response on time scales. With the help of a continuation theorem based on coincidence degree theory, we establish easily verifiable criteria for the existence of multiple periodic solutions. As corollaries, some applications are listed. In particular, our results improve and generalize some known ones.
Abstract: Calcium is very important for communication among
the neurons. It is vital in a number of cell processes such as secretion,
cell movement, cell differentiation. To reduce the system of reactiondiffusion
equations of [Ca2+] into a single equation, two theories
have been proposed one is excess buffer approximation (EBA) other
is rapid buffer approximation (RBA). The RBA is more realistic than
the EBA as it considers both the mobile and stationary endogenous
buffers. It is valid near the mouth of the channel. In this work we have
studied the effects of different types of buffers on calcium diffusion
under RBA. The novel thing studied is the effect of sodium ions on
calcium diffusion. The model has been made realistic by considering
factors such as variable [Ca2+], [Na+] sources, sodium-calcium
exchange protein(NCX), Sarcolemmal Calcium ATPase pump. The
proposed mathematical leads to a system of partial differential equations
which has been solved numerically to study the relationships
between different parameters such as buffer concentration, buffer
disassociation rate, calcium permeability. We have used Forward
Time Centred Space (FTCS) approach to solve the system of partial
differential equations.
Abstract: A feeding trial was conducted to investigate the effect
of periodically use of garlic on performance and carcass
characteristics in broiler chickens. 240 1-day-old Ross broiler chicks
randomly allocated into the 10 dietary treatments (A, B, C, D, E, F,
G, H, I and J) for 6 wk. Treatment A or control group, received basal
diet (based on standards of Ross management guidelines) without
supplementation of garlic powder while B, C and D dietary
treatments were basal diet supplemented with 0.5, 1 and 3% garlic
powder, respectively for the whole time of experiment (6 weeks).
Birds in group E, F and G were fed control diet supplemented with
0.5, 1 and 3% garlic powder, respectively just in their starter diet (0-
21d). Birds in three other treatments (H, I and J) received control diet
for the first 21 days and 0.5, 1 and 3% of garlic powder was added to
their finisher diets, respectively. 1 and 3% supplemented groups in
finisher period had better performance as compared with other
groups. Since present study conducted in optimum and antiseptic
conditions, it seems that better or more responses could be expected
in performance if the raising conditions would not be healthy.
Abstract: In this paper, some new nonlinear generalized
Gronwall-Bellman-Type integral inequalities with mixed time delays
are established. These inequalities can be used as handy tools
to research stability problems of delayed differential and integral
dynamic systems. As applications, based on these new established
inequalities, some p-stable results of a integro-differential equation
are also given. Two numerical examples are presented to illustrate
the validity of the main results.
Abstract: It is not a secret that, IT management has become
more and more and integrated part of almost all organizations. IT
managers posses an enormous amount of knowledge within both
organizational knowledge and general IT knowledge. This article
investigates how IT managers keep themselves updated on IT
knowledge in general and looks into how much time IT managers
spend on weekly basis searching the net for new or problem solving
IT knowledge. The theory used in this paper is used to investigate the
current role of IT managers and what issues they are facing.
Furthermore a research is conducted where 7 IT managers in medium
sized and large Danish companies are interviewed to add further
focus on the role of the IT manager and to focus on how they keep
themselves updated. Beside finding substantial need for more
research, IT managers – generalists or specialists – only have limited
knowledge resources at hand in updating their own knowledge –
leaving much initiative to vendors.
Abstract: Eye localization is necessary for face recognition and
related application areas. Most of eye localization algorithms reported
so far still need to be improved about precision and computational
time for successful applications. In this paper, we propose an eye
location method based on multi-scale Gabor feature vectors, which is
more robust with respect to initial points. The eye localization based
on Gabor feature vectors first needs to constructs an Eye Model Bunch
for each eye (left or right eye) which consists of n Gabor jets and
average eye coordinates of each eyes obtained from n model face
images, and then tries to localize eyes in an incoming face image by
utilizing the fact that the true eye coordinates is most likely to be very
close to the position where the Gabor jet will have the best Gabor jet
similarity matching with a Gabor jet in the Eye Model Bunch. Similar
ideas have been already proposed in such as EBGM (Elastic Bunch
Graph Matching). However, the method used in EBGM is known to be
not robust with respect to initial values and may need extensive search
range for achieving the required performance, but extensive search
ranges will cause much more computational burden. In this paper, we
propose a multi-scale approach with a little increased computational
burden where one first tries to localize eyes based on Gabor feature
vectors in a coarse face image obtained from down sampling of the
original face image, and then localize eyes based on Gabor feature
vectors in the original resolution face image by using the eye
coordinates localized in the coarse scaled image as initial points.
Several experiments and comparisons with other eye localization
methods reported in the other papers show the efficiency of our
proposed method.
Abstract: The purpose of this research is to develop a security model for voice eavesdropping protection over digital networks. The proposed model provides an encryption scheme and a personal secret key exchange between communicating parties, a so-called voice data transformation system, resulting in a real-privacy conversation. The operation of this system comprises two main steps as follows: The first one is the personal secret key exchange for using the keys in the data encryption process during conversation. The key owner could freely make his/her choice in key selection, so it is recommended that one should exchange a different key for a different conversational party, and record the key for each case into the memory provided in the client device. The next step is to set and record another personal option of encryption, either taking all frames or just partial frames, so-called the figure of 1:M. Using different personal secret keys and different sets of 1:M to different parties without the intervention of the service operator, would result in posing quite a big problem for any eavesdroppers who attempt to discover the key used during the conversation, especially in a short period of time. Thus, it is quite safe and effective to protect the case of voice eavesdropping. The results of the implementation indicate that the system can perform its function accurately as designed. In this regard, the proposed system is suitable for effective use in voice eavesdropping protection over digital networks, without any requirements to change presently existing network systems, mobile phone network and VoIP, for instance.
Abstract: Quantitative characterization of nonlinear directional
couplings between stochastic oscillators from data is considered. We
suggest coupling characteristics readily interpreted from a physical
viewpoint and their estimators. An expression for a statistical
significance level is derived analytically that allows reliable coupling
detection from a relatively short time series. Performance of the
technique is demonstrated in numerical experiments.
Abstract: In this paper the authors propose and verify an approach to control heat flow in machine tool components. Thermal deformations are a main aspect that affects the accuracy of machining. Due to goals of energy efficiency, thermal basic loads should be reduced. This leads to inhomogeneous and time variant temperature profiles. To counteract these negative consequences, material with high melting enthalpy is used as a method for thermal stabilization. The increased thermal capacity slows down the transient thermal behavior. To account for the delayed thermal equilibrium, a control mechanism for thermal flow is introduced. By varying a gap in a heat flow path the thermal resistance of an assembly can be controlled. This mechanism is evaluated in two experimental setups. First to validate the ability to control the thermal resistance and second to prove the possibility of a self-sufficient option based on the selfsensing abilities of thermal shape memory alloys.
Abstract: Visualizing “Courses – Pre – Required -
Architecture" on the screen has proven to be useful and helpful for
university actors and specially for students. In fact, these students
can easily identify courses and their pre required, perceive the
courses to follow in the future, and then can choose rapidly the
appropriate course to register in. Given a set of courses and their prerequired,
we present an algorithm for visualization a graph entitled
“Courses-Pre-Required-Graph" that present courses and their prerequired
in order to help students to recognize, lonely, what courses
to take in the future and perceive the contain of all courses that they
will study. Our algorithm using “Force Directed Placement"
technique visualizes the “Courses-Pre-Required-Graph" in such way
that courses are easily identifiable. The time complexity of our
drawing algorithm is O (n2), where n is the number of courses in the
“Courses-Pre-Required-Graph".
Abstract: Analysis for the generalized thermoelastic Lamb
waves, which propagates in anisotropic thin plates in generalized
thermoelasticity, is presented employing normal mode expansion
method. The displacement and temperature fields are expressed by a
summation of the symmetric and antisymmetric thermoelastic modes
in the surface thermal stresses and thermal gradient free orthotropic
plate, therefore the theory is particularly appropriate for waveform
analyses of Lamb waves in thin anisotropic plates. The transient
waveforms excited by the thermoelastic expansion are analyzed for
an orthotropic thin plate. The obtained results show that the theory
provides a quantitative analysis to characterize anisotropic
thermoelastic stiffness properties of plates by wave detection. Finally
numerical calculations have been presented for a NaF crystal, and the
dispersion curves for the lowest modes of the symmetric and
antisymmetric vibrations are represented graphically at different
values of thermal relaxation time. However, the methods can be used
for other materials as well
Abstract: It is estimated that the total cost of abnormal
conditions to US process industries is around $20 billion dollars in
annual losses. The hydrotreatment (HDT) of diesel fuel in petroleum
refineries is a conversion process that leads to high profitable
economical returns. However, this is a difficult process to control
because it is operated continuously, with high hydrogen pressures
and it is also subject to disturbances in feed properties and catalyst
performance. So, the automatic detection of fault and diagnosis plays
an important role in this context. In this work, a hybrid approach
based on neural networks together with a pos-processing
classification algorithm is used to detect faults in a simulated HDT
unit. Nine classes (8 faults and the normal operation) were correctly
classified using the proposed approach in a maximum time of 5
minutes, based on on-line data process measurements.
Abstract: Introduction applicability of high-speed cutting stock problem (CSP) is presented in this paper. Due to the orders continued coming in from various on-line ways for a professional cutting company, to stay competitive, such a business has to focus on sustained production at high levels. In others words, operators have to keep the machine running to stay ahead of the pack. Therefore, the continuous stock cutting problem with setup is proposed to minimize the cutting time and pattern changing time to meet the on-line given demand. In this paper, a novel method is proposed to solve the problem directly by using cutting patterns directly. A major advantage of the proposed method in series on-line production is that the system can adjust the cutting plan according to the floating orders. Examples with multiple items are demonstrated. The results show considerable efficiency and reliability in high-speed cutting of CSP.
Abstract: Optical burst switching(OBS) is considered as one of
preferable network technologies for the next generation Internet. The
Internet has two traffic classes, i.e. real-time bursts and reliable bursts.
It is an important subject for OBS to achieve cooperated operation of
real-time bursts and reliable bursts. In this paper, we proposes a new
effective traffic control method named Separate TB+LB (Token
Bucket + Leaky Bucket : TB+LB) method. The proposed method
presents a new Token Bucket scheme for real-time bursts called as
RBO-TB (Real-time Bursts Oriented Token Bucket). The method also
applies the LB method to reliable bursts for obtaining better
performance. This paper verifies the effectiveness of the Separate
TB+LB method through the performance evaluation.
Abstract: Here, a new idea to speed up the operation of
complex valued time delay neural networks is presented. The whole
data are collected together in a long vector and then tested as a one
input pattern. The proposed fast complex valued time delay neural
networks uses cross correlation in the frequency domain between the
tested data and the input weights of neural networks. It is proved
mathematically that the number of computation steps required for
the presented fast complex valued time delay neural networks is less
than that needed by classical time delay neural networks. Simulation
results using MATLAB confirm the theoretical computations.
Abstract: The reduction of hexavalent chromium by scrap iron
was investigated in continuous system, using long-term column
experiments, for aqueous Cr(VI) solutions having low buffering
capacities, over the Cr(VI) concentration range of 5 – 40 mg/L. The
results showed that the initial Cr(VI) concentration significantly
affects the reduction capacity of scrap iron. Maximum reduction
capacity of scrap iron was observed at the beginning of the column
experiments; the lower the Cr(VI) concentration, the greater the
experiment duration with maximum scrap iron reduction capacity.
However, due to passivation of active surface, scrap iron reduction
capacity continuously decreased in time, especially after Cr(VI)
breakthrough. The experimental results showed that highest
reduction capacity recorded until Cr(VI) breakthrough was 22.8 mg
Cr(VI)/g scrap iron, at CI = 5 mg/L, and decreased with increasing
Cr(VI) concentration. In order to assure total reduction of greater
Cr(VI) concentrations for a longer period of time, either the mass of
scrap iron filling, or the hydraulic retention time should be increased.
Abstract: The reliability of distributed systems and computer
networks have been modeled by a probabilistic network or a graph G.
Computing the residual connectedness reliability (RCR), denoted by
R(G), under the node fault model is very useful, but is an NP-hard
problem. Since it may need exponential time of the network size to
compute the exact value of R(G), it is important to calculate its tight
approximate value, especially its lower bound, at a moderate
calculation time. In this paper, we propose an efficient algorithm for
reliability lower bound of distributed systems with unreliable nodes.
We also applied our algorithm to several typical classes of networks
to evaluate the lower bounds and show the effectiveness of our
algorithm.
Abstract: Erwinia carotovora var. carotovora is the main cause of soft rot in potatoes. Hyphaene thebaica was studied for biocontrol of E. carotovora which inhibited growth of E. carotovora on solid medium, a comparative study of classical and ultrasound-assisted extractions of Hyphaene thebaica fruit. The use of ultrasound decreased significant the total time of treatment and increase the total amount of crude extract. The crude extract was subjected to determine the in vitro, by a bioassay technique revealed that the treatment of paper disks with ultrasound extraction of Hyphaene thebaica reduced the growth of pathogen and produced inhibition zones up to 38mm in diameter. The antioxidant activity of ultrasound-ethanolic extract of Doum fruits (Hyphaene thebaica) was determined. Data obtained showed that the extract contains the secondary metabolites such as Tannins, Saponin, Flavonoids, Phenols, Steroids, Terpenoids, Glycosides and Alkaloids.
Abstract: The progress of concentrations of particular heavy metals was assessed in chosen localities in region Moravia, the Czech Republic, from 2007 to 2009. Particular metals were observed in localities with various types and characterization of zone. Pb, Ni, As and Cd were emphasized as a result of their toxicity and potential adverse health effect to the exposed population. The progress of metal concentrations and their health effects in the most polluted localities were examined. According to the results, the air pollution limit values were not exceeded. Based on the health risk assessment, the probability of developing tumorous diseases is acceptable, except for the increased probability of cancer risk from long-term exposure to As.
Abstract: This study presents the application of artificial
neural network for modeling the phenolic compound
migration through vertical soil column. A three layered feed
forward neural network with back propagation training
algorithm was developed using forty eight experimental data
sets obtained from laboratory fixed bed vertical column tests.
The input parameters used in the model were the influent
concentration of phenol(mg/L) on the top end of the soil
column, depth of the soil column (cm), elapsed time after
phenol injection (hr), percentage of clay (%), percentage of
silt (%) in soils. The output of the ANN was the effluent
phenol concentration (mg/L) from the bottom end of the soil
columns. The ANN predicted results were compared with the
experimental results of the laboratory tests and the accuracy of
the ANN model was evaluated.