Abstract: In this paper, the Lennard -Jones potential is applied
to molecules of liquid argon as well as its vapor and platinum as solid
surface in order to perform a non-equilibrium molecular dynamics
simulation to study the microscopic aspects of liquid-vapor-solid
interactions. The channel is periodic in x and y directions and along z
direction it is bounded by atomic walls. It was found that density of
the liquids near the solid walls fluctuated greatly and that the
structure was more like a solid than a liquid. This indicates that the
interactions of solid and liquid molecules are very strong. The
resultant surface tension, liquid density and vapor density are found
to be well predicted when compared with the experimental data for
argon. Liquid and vapor densities were found to depend on the cutoff
radius which induces the use of P3M (particle-particle particle-mesh)
method which was implemented for evaluation of force and surface
tension.
Abstract: Research into the problem of classification of sonar signals has been taken up as a challenging task for the neural networks. This paper investigates the design of an optimal classifier using a Multi layer Perceptron Neural Network (MLP NN) and Support Vector Machines (SVM). Results obtained using sonar data sets suggest that SVM classifier perform well in comparison with well-known MLP NN classifier. An average classification accuracy of 91.974% is achieved with SVM classifier and 90.3609% with MLP NN classifier, on the test instances. The area under the Receiver Operating Characteristics (ROC) curve for the proposed SVM classifier on test data set is found as 0.981183, which is very close to unity and this clearly confirms the excellent quality of the proposed classifier. The SVM classifier employed in this paper is implemented using kernel Adatron algorithm is seen to be robust and relatively insensitive to the parameter initialization in comparison to MLP NN.
Abstract: Reliable information about tool temperature
distribution is of central importance in metal cutting. In this study,
tool-chip interface temperature was determined in cutting of ST37
steel workpiece by applying HSS as the cutting tool in dry turning.
Two different approaches were implemented for temperature
measuring: an embedded thermocouple (RTD) in to the cutting tool
and infrared (IR) camera. Comparisons are made between
experimental data and results of MSC.SuperForm and FLUENT
software.
An investigation of heat generation in cutting tool was performed
by varying cutting parameters at the stable cutting tool geometry and
results were saved in a computer; then the diagrams of tool
temperature vs. various cutting parameters were obtained. The
experimental results reveal that the main factors of the increasing
cutting temperature are cutting speed (V ), feed rate ( S ) and depth
of cut ( h ), respectively. It was also determined that simultaneously
change in cutting speed and feed rate has the maximum effect on
increasing cutting temperature.
Abstract: Using steelmaking slag as a raw material, aragonite superstructure product had been synthesized via an indirect CO2 mineral sequestration rout. It mainly involved two separate steps, in which the element of calcium is first selectively leached from steelmaking slag by a novel leaching media consisting of organic solvent Tributyl phosphate (TBP), acetic acid, and ultra-purity water, followed by enhanced carbonation in a separate step for aragonite superstructure production as well as efficiency recovery of leaching media. Based on the different leaching medium employed in the steelmaking slag leaching process, two typical products were collected from the enhanced carbonation step. The products were characterized by X-ray powder diffraction (XRD) and scanning electron microscopy (SEM), respectively. It reveals that the needle-like aragonite crystals self-organized into aragonite superstructure particles including aragonite microspheres as well as dumbbell-like spherical particles, can be obtained from the steelmaking slag with the purity over 99%.
Abstract: This paper gives a novel method for improving
classification performance for cancer classification with very few
microarray Gene expression data. The method employs classification
with individual gene ranking and gene subset ranking. For selection
and classification, the proposed method uses the same classifier. The
method is applied to three publicly available cancer gene expression
datasets from Lymphoma, Liver and Leukaemia datasets. Three
different classifiers namely Support vector machines-one against all
(SVM-OAA), K nearest neighbour (KNN) and Linear Discriminant
analysis (LDA) were tested and the results indicate the improvement
in performance of SVM-OAA classifier with satisfactory results on
all the three datasets when compared with the other two classifiers.
Abstract: this paper presented a survey analysis subjected on
network bandwidth management from published papers referred in
IEEE Explorer database in three years from 2009 to 2011. Network
Bandwidth Management is discussed in today-s issues for computer
engineering applications and systems. Detailed comparison is
presented between published papers to look further in the IP based
network critical research area for network bandwidth management.
Important information such as the network focus area, a few
modeling in the IP Based Network and filtering or scheduling used in
the network applications layer is presented. Many researches on
bandwidth management have been done in the broad network area
but fewer are done in IP Based network specifically at the
applications network layer. A few researches has contributed new
scheme or enhanced modeling but still the issue of bandwidth
management still arise at the applications network layer. This survey
is taken as a basic research towards implementations of network
bandwidth management technique, new framework model and
scheduling scheme or algorithm in an IP Based network which will
focus in a control bandwidth mechanism in prioritizing the network
traffic the applications layer.
Abstract: A common way to elude the signature-based Network Intrusion Detection System is based upon changing a recognizable attack to an unrecognizable one via the IDS. For example, in order to evade sign accommodation with intrusion detection system markers, a hacker spilt the payload packet into many small pieces or hides them within messages. In this paper we try to model the main fragmentation attack and create a new module in the intrusion detection architecture system which recognizes the main fragmentation attacks through verification of integrity checking of TCP packet in order to prevent elusion of the system and also to announce the necessary alert to the system administrator.
Abstract: The most reliable and accurate description of the actual behavior of a software system is its source code. However, not all questions about the system can be answered directly by resorting to this repository of information. What the reverse engineering methodology aims at is the extraction of abstract, goal-oriented “views" of the system, able to summarize relevant properties of the computation performed by the program. While concentrating on reverse engineering we had modeled the C++ files by designing the translator.
Abstract: A New features are extracted and compared to
improve the prediction of protein-protein interactions. The basic idea
is to select and use the best set of features from the Tensor matrices
that are produced by the frequency vectors of the protein sequences.
Three set of features are compared, the first set is based on the
indices that are the most common in the interacting proteins, the
second set is based on the indices that tend to be common in the
interacting and non-interacting proteins, and the third set is
constructed by using random indices. Moreover, three encoding
strategies are compared; that are based on the amino asides polarity,
structure, and chemical properties. The experimental results indicate
that the highest accuracy can be obtained by using random indices
with chemical properties encoding strategy and support vector
machine.
Abstract: Forty-five dairy cows were used to compare the
enzyme activity of alkaline phosphatase (ALP), lactate
dehydrogenase (LDH), α -amylase in the cervical mucus of cows
during spontaneous and induced estrus using progestagen or PGF2 α
and to determine whether these enzymes affect the fertility in cows
with induced estrus, at the time of Al. The animals were assigned to 3
groups (no treatment, a Crestar® for 12 days, a double im injection of
PGF2 α). The cows were artificially inseminated (AI). Cervical
mucus samples were collected from all cows 3 to 5 min before the
AI. The results are summarized as follows: ALP and α -amylase
activity for spontaneous estrus were similar to those for induced
estrus (P>0.05) . LDH activity levels during spontaneous and PGF2 α
induced estrus was significantly lower (P < 0.001) than that in
progestagene induced estrus groups. While no difference was found
between the first and the third groups. Our result showed a significant
difference in LDH activity levels between cows conceived with 2 or
more AI and those conceived with 1 AI. The result of this study
showed that the enzyme activity in cervical mucus is helpful for
detection of ovulation and time of AI.
Abstract: The experimental study of position control of a light
weight and small size robotic finger during non-contact motion is
presented in this paper. The finger possesses fingertip pinching and
self adaptive grasping capabilities, and is made of a seven bar linkage
mechanism with a slider in the middle phalanx. The control system is
tested under the Proportional Integral Derivative (PID) control
algorithm and Recursive Least Square (RLS) based Feedback Error
Learning (FEL) control scheme to overcome the uncertainties present
in the plant. The experiments conducted in Matlab Simulink and xPC
Target environments show that the overall control strategy is efficient
in controlling the finger movement.
Abstract: To establish optical communication between any two
satellites, the transmitter satellite must track the beacon of the
receiver satellite and point the information optical beam in its
direction. Optical tracking and pointing systems for free space suffer
during tracking from high-amplitude vibration because of
background radiation from interstellar objects such as the Sun, Moon,
Earth, and stars in the tracking field of view or the mechanical
impact from satellite internal and external sources. The vibrations of
beam pointing increase the bit error rate and jam communication
between the two satellites. One way to overcome this problem is the
use of very small transmitter beam divergence angles of too narrow
divergence angle is that the transmitter beam may sometimes miss
the receiver satellite, due to pointing vibrations. In this paper we
propose the use of genetic algorithm to optimize the BER as function
of transmitter optics aperture.
Abstract: The company-s ability to draw on a range of external
sources to meet their needs for innovation, has been termed 'open
innovation' (OI). Very few empirical analyses have been conducted
on Small and Medium Enterprises (SMEs) to the extent that they
describe and understand the characteristics and implications of this
new paradigm.
The study's objective is to identify and characterize different
modes of OI, (considering innovation process phases and the variety
and breadth of the collaboration), determinants, barriers and
motivations in SMEs. Therefore a survey was carried out among
Italian manufacturing firms and a database of 105 companies was
obtained. With regard to data elaboration, a factorial and cluster
analysis has been conducted and three different OI modes have
emerged: selective low open, unselective open upstream, and mid-
partners integrated open. The different behaviours of the three
clusters in terms of determinants factors, performance, firm-s
technology intensity, barriers and motivations have been analyzed
and discussed.
Abstract: The aim of this paper is to present a comparative
study on two different methods for the evaluation of the equilibrium
point of a ship, core issue for designing an On Board Stability System
(OBSS) module that, starting from geometry information of a ship
hull, described by a discrete model in a standard format, and the
distribution of all weights onboard calculates the ship floating
conditions (in draught, heel and trim).
Abstract: Nowadays use of a new structural bracing system
called 'Knee Bracing System' have taken the specialists attention too
much. On the other hand nonlinear static analysis procedures in
estimate structures performance in earthquake time have taken
attention too much. One of these procedure is modal pushover
analysis (MPA) procedure. The accuracy of MPA procedure for
simple steel moment resisting frame has been verified and considered
in Chintanapakdee and Chopra-s article in 2003. Since the accuracy
of MPA procedure has not verified for semi-rigid steel frames with
knee bracing, we are going to get through with this matter in this
study. For this purpose, the selected structures are four frames with
different heights, 5 to 20 stories, will be designed according to AISC
criteria. Then MPA procedure is used for the same frames with
different rigidity percentiles of connections. The results of seismic
responses are compared with dynamic nonlinear response history
analysis as exact procedure and accuracy of MPA procedure is
evaluated. It seems that MPA procedure accuracy will come down by
reduction of the rigidity percentiles of semi-rigid connections.
Abstract: This paper addresses one of the most important issues
have been considered in hybrid MTS/MTO production environments. To cope with the problem, a mathematical programming model is
applied from a tactical point of view. The model is converted to a fuzzy goal programming model, because a degree of uncertainty is involved in hybrid MTS/MTO context. Finally, application of the
proposed model in an industrial center is reported and the results prove the validity of the model.
Abstract: This research work takes a different approach in
the discussion of urban form impacts on transport planning and
auto dependency. Concentrated density represented by effective
density explains auto dependency better than the conventional
density and it is proved to be a realistic density representative for
the urban transportation analysis. Model analysis reveals that
effective density is influenced by the shopping accessibility
index as well as job density factor. It is also combined with the
job access variable to classify four levels of Transport Activity
Centers (TACs) in Okinawa, Japan. Trip attraction capacity and
levels of the newly classified TACs was found agreeable with the
amount of daily trips attracted to each center. The trip attraction
data set was drawn from a 2007 Okinawa personal trip survey.
This research suggests a planning methodology which guides
logical transport supply routes and concentrated local
development schemes.
Abstract: The purpose of this study was to investigate the
relationships among students- process of study, creative self-efficacy
and creativity while attending college. A total of 60 students enrolled
in Hsiuping Institute of Technology in central Taiwan were selected as
samples for the study. The instruments for this study included three
questionnaires to explore the aforesaid aspects.
This researchers tested creative self-efficacy and process of study,
and creativity with Pearson correlation and hierarchical regression
analyses. The major findings of this research are (1) the process of
study had direct positive predictability on creativity, and (2) the
relationship between process of study and creativity is partially
mediated by creative self-efficacy.
Abstract: This paper investigates the performance of a speech
recognizer in an interactive voice response system for various coded
speech signals, coded by using a vector quantization technique namely
Multi Switched Split Vector Quantization Technique. The process of
recognizing the coded output can be used in Voice banking application.
The recognition technique used for the recognition of the coded speech
signals is the Hidden Markov Model technique. The spectral distortion
performance, computational complexity, and memory requirements of
Multi Switched Split Vector Quantization Technique and the
performance of the speech recognizer at various bit rates have been
computed. From results it is found that the speech recognizer is
showing better performance at 24 bits/frame and it is found that the
percentage of recognition is being varied from 100% to 93.33% for
various bit rates.
Abstract: Let p be a prime number, Fpbe a finite field and let Qpdenote the set of quadratic residues in Fp. In the first section we givesome notations and preliminaries from elliptic curves. In the secondsection, we consider some properties of rational points on ellipticcurves Ep,b: y2= x3+ b2 over Fp, where b ∈ F*p. Recall that theorder of Ep,bover Fpis p + 1 if p ≡ 5(mod 6). We generalize thisresult to any field Fnp for an integer n≥ 2. Further we obtain someresults concerning the sum Σ[x]Ep,b(Fp) and Σ[y]Ep,b(Fp), thesum of x- and y- coordinates of all points (x, y) on Ep,b, and alsothe the sum Σ(x,0)Ep,b(Fp), the sum of points (x, 0) on Ep,b.