Abstract: In the context of computer numerical control (CNC) and computer aided manufacturing (CAM), the capabilities of programming languages such as symbolic and intuitive programming, program portability and geometrical portfolio have special importance. They allow to save time and to avoid errors during part programming and permit code re-usage. Our updated literature review indicates that the current state of art presents voids in parametric programming, program portability and programming flexibility. In response to this situation, this article presents a compiler implementation for EGCL (Extended G-code Language), a new, enriched CNC programming language which allows the use of descriptive variable names, geometrical functions and flow-control statements (if-then-else, while). Our compiler produces low-level generic, elementary ISO-compliant Gcode, thus allowing for flexibility in the choice of the executing CNC machine and in portability. Our results show that readable variable names and flow control statements allow a simplified and intuitive part programming and permit re-usage of the programs. Future work includes allowing the programmer to define own functions in terms of EGCL, in contrast to the current status of having them as library built-in functions.
Abstract: The main objective of seismic rehabilitation in the
foundations is decreasing the range of horizontal and vertical
vibrations and omitting high frequencies contents under the seismic
loading. In this regard, the advantages of micropiles network is
utilized. Reduction in vibration range of foundation can be achieved
by using high dynamic rigidness module such as deep foundations. In
addition, natural frequency of pile and soil system increases in regard
to rising of system rigidness. Accordingly, the main strategy is
decreasing of horizontal and vertical seismic vibrations of the
structure. In this case, considering the impact of foundation, pile and
improved soil foundation is a primary concern. Therefore, in this
paper, effective factors are studied on the seismic rehabilitation of
foundations applying network micropiles in sandy soils with
nonlinear reaction.
Abstract: Firstly, this study briefly presents the current situation that there exists a vast gap between current Chinese and Japanese seismic design specification for bridge pile foundation in liquefiable and liquefaction-induced lateral spreading ground; The Chinese and Japanese seismic design method and technical detail for bridge pile foundation in liquefying and lateral spreading ground are described and compared systematically and comprehensively, the methods of determining coefficient of subgrade reaction and its reduction factor as well as the computing mode of the applied force on pile foundation due to liquefaction-induced lateral spreading soil in Japanese design specification are especially introduced. Subsequently, the comparison indicates that the content of Chinese seismic design specification for bridge pile foundation in liquefiable and liquefaction-induced lateral spreading ground, just presenting some qualitative items, is too general and lacks systematicness and maneuverability. Finally, some defects of seismic design specification in China are summarized, so the improvement and revision of specification in the field turns out to be imperative for China, some key problems of current Chinese specifications are generalized and the corresponding improvement suggestions are proposed.
Abstract: Choosing the right metadata is a critical, as good
information (metadata) attached to an image will facilitate its
visibility from a pile of other images. The image-s value is enhanced
not only by the quality of attached metadata but also by the technique
of the search. This study proposes a technique that is simple but
efficient to predict a single human image from a website using the
basic image data and the embedded metadata of the image-s content
appearing on web pages. The result is very encouraging with the
prediction accuracy of 95%. This technique may become a great
assist to librarians, researchers and many others for automatically and
efficiently identifying a set of human images out of a greater set of
images.
Abstract: Decrease in hardware costs and advances in computer
networking technologies have led to increased interest in the use of
large-scale parallel and distributed computing systems. One of the
biggest issues in such systems is the development of effective
techniques/algorithms for the distribution of the processes/load of a
parallel program on multiple hosts to achieve goal(s) such as
minimizing execution time, minimizing communication delays,
maximizing resource utilization and maximizing throughput.
Substantive research using queuing analysis and assuming job
arrivals following a Poisson pattern, have shown that in a multi-host
system the probability of one of the hosts being idle while other host
has multiple jobs queued up can be very high. Such imbalances in
system load suggest that performance can be improved by either
transferring jobs from the currently heavily loaded hosts to the lightly
loaded ones or distributing load evenly/fairly among the hosts .The
algorithms known as load balancing algorithms, helps to achieve the
above said goal(s). These algorithms come into two basic categories -
static and dynamic. Whereas static load balancing algorithms (SLB)
take decisions regarding assignment of tasks to processors based on
the average estimated values of process execution times and
communication delays at compile time, Dynamic load balancing
algorithms (DLB) are adaptive to changing situations and take
decisions at run time.
The objective of this paper work is to identify qualitative
parameters for the comparison of above said algorithms. In future this
work can be extended to develop an experimental environment to
study these Load balancing algorithms based on comparative
parameters quantitatively.
Abstract: Infrared communication in the wavelength band 780-
950 nm is very suitable for short-range point-to-point communications.
It is a good choice for vehicle-to-vehicle communication in several
intelligent-transportation-system (ITS) applications such as cooperative
driving, collision warning, and pileup-crash prevention. In this
paper, with the aid of a physical model established in our previous
works, we explore the communication area of an infrared intervehicle
communication system utilizing a typical low-cost cormmercial lightemitting
diodes (LEDs) as the emitter and planar p-i-n photodiodes
as the receiver. The radiation pattern of the emitter fabricated by
aforementioned LEDs and the receiving pattern of the receiver are
approximated by a linear combination of cosinen functions. This
approximation helps us analyze the system performance easily. Both
multilane straight-road conditions and curved-road conditions with
various radius of curvature are taken into account. The condition of
a small car communicating with a big truck, i.e., there is a vertical
mounting height difference between the emitter and the receiver, is
also considered. Our results show that the performance of the system
meets the requirement of aforementioned ITS applications in terms
of the communication area.
Abstract: Model-checking tools such as Symbolic Model Verifier
(SMV) and NuSMV are available for checking hardware designs.
These tools can automatically check the formal legitimacy of a
design. However, NuSMV is too low level for describing a complete
hardware design. It is therefore necessary to translate the system
definition, as designed in a language such as Verilog or VHDL, into
a language such as NuSMV for validation. In this paper, we present
a meta hardware description language, Melasy, that contains a code
generator for existing hardware description languages (HDLs) and
languages for model checking that solve this problem.
Abstract: Most scientific programs have large input and output
data sets that require out-of-core programming or use virtual memory
management (VMM). Out-of-core programming is very error-prone
and tedious; as a result, it is generally avoided. However, in many
instance, VMM is not an effective approach because it often results
in substantial performance reduction. In contrast, compiler driven I/O
management will allow a program-s data sets to be retrieved in parts,
called blocks or tiles. Comanche (COmpiler MANaged caCHE) is a
compiler combined with a user level runtime system that can be used
to replace standard VMM for out-of-core programs. We describe
Comanche and demonstrate on a number of representative problems
that it substantially out-performs VMM. Significantly our system
does not require any special services from the operating system and
does not require modification of the operating system kernel.
Abstract: Understanding proteins functions is a major goal in
the post-genomic era. Proteins usually work in context of other
proteins and rarely function alone. Therefore, it is highly relevant to
study the interaction partners of a protein in order to understand its
function. Machine learning techniques have been widely applied to
predict protein-protein interactions. Kernel functions play an
important role for a successful machine learning technique. Choosing
the appropriate kernel function can lead to a better accuracy in a
binary classifier such as the support vector machines. In this paper,
we describe a Bayesian kernel for the support vector machine to
predict protein-protein interactions. The use of Bayesian kernel can
improve the classifier performance by incorporating the probability
characteristic of the available experimental protein-protein
interactions data that were compiled from different sources. In
addition, the probabilistic output from the Bayesian kernel can assist
biologists to conduct more research on the highly predicted
interactions. The results show that the accuracy of the classifier has
been improved using the Bayesian kernel compared to the standard
SVM kernels. These results imply that protein-protein interaction can
be predicted using Bayesian kernel with better accuracy compared to
the standard SVM kernels.
Abstract: Leonotisleonurus a shrub indigenous to Southern
Africa is widely used in traditional medicine to treat a variety of
conditions ranging from skin diseases and cough to epileptic fits and
‘heart problems’. Studies on the aqueous extract of the leaves have
indicated cycloxegenase enzyme inhibitory activity and an
antihypertensive effect.
Five methanol leaf extract fractions (MLEa - MLEe) of L.
leonurus were tested on anaesthetized normotensive male Wistar rats
(AWR) and isolated perfused working rat hearts (IWH). Fraction
MLEc (0.01mg/kg – 0.05mg/kg) induced significant increases in BP
and HR in AWR and positive chronotropic and inotropic effects in
IWH (1.0mg/ml – 5.0mg/ml). Pre-administration of atenolol
(2.0mg/kg) and prazosin (60μg/kg) significantly inhibited MLEc
effect on HR and MAP respectively in vivo, while atenolol
(7.0mg/ml) pre-perfusion significantly inhibited MLEc effect in vitro.
The hypertensive effect of MLEc is probably via β1agonism.
Results also indicate the presence of multiple cardioactive
compounds in L. leonurus.
Abstract: We present the development of a system of programs designed for the compilation and execution of applications for handheld computers. In introduction we describe the purpose of the project and its components. The next two paragraphs present the first two components of the project (the scanner and parser generators). Then we describe the Object Pascal compiler and the virtual machines for Windows and Palm OS. In conclusion we emphasize the ways in which the project can be extended.
Abstract: Unlike general-purpose processors, digital signal
processors (DSP processors) are strongly application-dependent. To
meet the needs for diverse applications, a wide variety of DSP
processors based on different architectures ranging from the
traditional to VLIW have been introduced to the market over the
years. The functionality, performance, and cost of these processors
vary over a wide range. In order to select a processor that meets the
design criteria for an application, processor performance is usually
the major concern for digital signal processing (DSP) application
developers. Performance data are also essential for the designers of
DSP processors to improve their design. Consequently, several DSP
performance benchmarks have been proposed over the past decade or
so. However, none of these benchmarks seem to have included recent
new DSP applications.
In this paper, we use a new benchmark that we recently developed
to compare the performance of popular DSP processors from Texas
Instruments and StarCore. The new benchmark is based on the
Selectable Mode Vocoder (SMV), a speech-coding program from the
recent third generation (3G) wireless voice applications. All
benchmark kernels are compiled by the compilers of the respective
DSP processors and run on their simulators. Weighted arithmetic
mean of clock cycles and arithmetic mean of code size are used to
compare the performance of five DSP processors.
In addition, we studied how the performance of a processor is
affected by code structure, features of processor architecture and
optimization of compiler. The extensive experimental data gathered,
analyzed, and presented in this paper should be helpful for DSP
processor and compiler designers to meet their specific design goals.
Abstract: In this paper, a wavelet-based neural network (WNN) classifier for recognizing EEG signals is implemented and tested under three sets EEG signals (healthy subjects, patients with epilepsy and patients with epileptic syndrome during the seizure). First, the Discrete Wavelet Transform (DWT) with the Multi-Resolution Analysis (MRA) is applied to decompose EEG signal at resolution levels of the components of the EEG signal (δ, θ, α, β and γ) and the Parseval-s theorem are employed to extract the percentage distribution of energy features of the EEG signal at different resolution levels. Second, the neural network (NN) classifies these extracted features to identify the EEGs type according to the percentage distribution of energy features. The performance of the proposed algorithm has been evaluated using in total 300 EEG signals. The results showed that the proposed classifier has the ability of recognizing and classifying EEG signals efficiently.
Abstract: Memory forensic is important in digital investigation.
The forensic is based on the data stored in physical memory that
involve memory management and processing time. However, the
current forensic tools do not consider the efficiency in terms of
storage management and the processing time. This paper shows the
high redundancy of data found in the physical memory that cause
inefficiency in processing time and memory management. The
experiment is done using Borland C compiler on Windows XP with
512 MB of physical memory.
Abstract: Increase in using internet makes some problems that
one of them is "internet anxiety". Internet anxiety is a type of anxious
that people may feel during surfing internet or using internet for their
educational purpose, blogging or streaming to digital libraries. The
goal of this study is evaluating of internet anxiety among the
management students. In this research Ealy's internet anxiety
questionnaire, consists of positive and negative items, is completed
by 310 participants. According to the findings, about 64.7% of them
were equal or below to mean anxiety score (50). The distribution of
internet anxiety scores was normal and there was no meaningful
difference between men-s and women's anxiety level in this sample.
Results also showed that there is no meaningful difference of internet
anxiety level between different fields of study in Management. This
evaluation will help managers to perform gap analysis between the
existent level and the desired one. Future work would be providing
techniques for abating human anxiety while using internet via human
computer interaction techniques.
Abstract: Streaming Applications usually run in parallel or in
series that incrementally transform a stream of input data. It poses a
design challenge to break such an application into distinguishable
blocks and then to map them into independent hardware processing
elements. For this, there is required a generic controller that
automatically maps such a stream of data into independent processing
elements without any dependencies and manual considerations. In
this paper, Kahn Process Networks (KPN) for such streaming
applications is designed and developed that will be mapped on
MPSoC. This is designed in such a way that there is a generic Cbased
compiler that will take the mapping specifications as an input
from the user and then it will automate these design constraints and
automatically generate the synthesized RTL optimized code for
specified application.
Abstract: Cerium-doped lanthanum bromide LaBr3:Ce(5%)
crystals are considered to be one of the most advanced scintillator
materials used in PET scanning, combining a high light yield, fast
decay time and excellent energy resolution. Apart from the correct
choice of scintillator, it is also important to optimise the detector
geometry, not least in terms of source-to-detector distance in order to
obtain reliable measurements and efficiency. In this study a
commercially available 25 mm x 25 mm BrilLanCeTM 380 LaBr3: Ce
(5%) detector was characterised in terms of its efficiency at varying
source-to-detector distances. Gamma-ray spectra of 22Na, 60Co, and
137Cs were separately acquired at distances of 5, 10, 15, and 20cm. As
a result of the change in solid angle subtended by the detector, the
geometric efficiency reduced in efficiency with increasing distance.
High efficiencies at low distances can cause pulse pile-up when
subsequent photons are detected before previously detected events
have decayed. To reduce this systematic error the source-to-detector
distance should be balanced between efficiency and pulse pile-up
suppression as otherwise pile-up corrections would need to be
necessary at short distances. In addition to the experimental
measurements Monte Carlo simulations have been carried out for the
same setup, allowing a comparison of results. The advantages and
disadvantages of each approach have been highlighted.
Abstract: In order to study pressed pile test and ultimate bearing
capacity character of large-diameter steel pipe pile, based on two high-piled wharfs of Zhanjiang Port, pressed pile test and numerical simulation of three large-diameter steel pipe piles are analyzed in this
paper. Anchored pile method is used to pressed pile test, and the
curves of Q-s and ultimate bearing capacity are attained. Then the three piles are numerically simulated by ABAQUS, and results of numerical simulation and those of field test are comparatively analyzed. The results show that settlement value of numerical
simulation is larger than that of field test in the process of loading, the difference value is widening with the increasing of load, and the
ultimate difference value of settlement is 20% to 30%.
Abstract: Computers are being integrated in the various aspects
of human every day life in different shapes and abilities. This fact
has intensified a requirement for the software development
technologies which is ability to be: 1) portable, 2) adaptable, and 3)
simple to develop. This problem is also known as the Pervasive
Computing Problem (PCP) which can be implemented in different
ways, each has its own pros and cons and Context Oriented
Programming (COP) is one of the methods to address the PCP.
In this paper a design for a COP framework, a context aware
framework, is presented which has eliminated weak points of a
previous design based on interpreter languages, while introducing the
compiler languages power in implementing these frameworks.
The key point of this improvement is combining COP and
Dependency Injection (DI) techniques. Both old and new frameworks
are analyzed to show advantages and disadvantages. Finally a
simulation of both designs is proposed to indicating that the practical
results agree with the theoretical analysis while the new design runs
almost 8 times faster.
Abstract: Dr Eliyahu Goldratt has done the pioneering work in
the development of Theory of Constraints. Since then, many more
researchers around the globe are working to enhance this body of
knowledge. In this paper, an attempt has been made to compile the
salient features of this theory from the work done by Goldratt and
other researchers. This paper will provide a good starting point to the
potential researchers interested to work in Theory of Constraints. The
paper will also help the practicing managers by clarifying their
concepts on the theory and will facilitate its successful
implementation in their working areas.