Abstract: Code mobility technologies attract more and more developers and consumers. Numerous domains are concerned, many platforms are developed and interest applications are realized. However, developing good software products requires modeling, analyzing and proving steps. The choice of models and modeling languages is so critical on these steps. Formal tools are powerful in analyzing and proving steps. However, poorness of classical modeling language to model mobility requires proposition of new models. The objective of this paper is to provide a specific formalism “Coloured Reconfigurable Nets" and to show how this one seems to be adequate to model different kinds of code mobility.
Abstract: Microscopic emission and fuel consumption models
have been widely recognized as an effective method to quantify real
traffic emission and energy consumption when they are applied with
microscopic traffic simulation models. This paper presents a
framework for developing the Microscopic Emission (HC, CO, NOx,
and CO2) and Fuel consumption (MEF) models for light-duty
vehicles. The variable of composite acceleration is introduced into
the MEF model with the purpose of capturing the effects of historical
accelerations interacting with current speed on emission and fuel
consumption. The MEF model is calibrated by multivariate
least-squares method for two types of light-duty vehicle using
on-board data collected in Beijing, China by a Portable Emission
Measurement System (PEMS). The instantaneous validation results
shows the MEF model performs better with lower Mean Absolute
Percentage Error (MAPE) compared to other two models. Moreover,
the aggregate validation results tells the MEF model produces
reasonable estimations compared to actual measurements with
prediction errors within 12%, 10%, 19%, and 9% for HC, CO, NOx
emissions and fuel consumption, respectively.
Abstract: Vortices can develop in intakes of turbojet and turbo
fan aero engines during high power operation in the vicinity of solid
surfaces. These vortices can cause catastrophic damage to the engine.
The factors determining the formation of the vortex include both
geometric dimensions as well as flow parameters. It was shown that
the threshold at which the vortex forms or disappears is also
dependent on the initial flow condition (i.e. whether a vortex forms
after stabilised non vortex flow or vice-versa). A computational fluid
dynamics study was conducted to determine the difference in
thresholds between the two conditions. This is the first reported
numerical investigation of the “memory effect". The numerical
results reproduce the phenomenon reported in previous experimental
studies and additional factors, which had not been previously studied,
were investigated. They are the rate at which ambient velocity
changes and the initial value of ambient velocity. The former was
found to cause a shift in the threshold but not the later. It was also
found that the varying condition thresholds are not symmetrical about
the neutral threshold. The vortex to no vortex threshold lie slightly
further away from the neutral threshold compared to the no vortex to
vortex threshold. The results suggests that experimental investigation
of vortex formation threshold performed either in vortex to no vortex
conditions, or vice versa, solely may introduce mis-predictions
greater than 10%.
Abstract: The use of neural networks for recognition application is generally constrained by their inherent parameters inflexibility after the training phase. This means no adaptation is accommodated for input variations that have any influence on the network parameters. Attempts were made in this work to design a neural network that includes an additional mechanism that adjusts the threshold values according to the input pattern variations. The new approach is based on splitting the whole network into two subnets; main traditional net and a supportive net. The first deals with the required output of trained patterns with predefined settings, while the second tolerates output generation dynamically with tuning capability for any newly applied input. This tuning comes in the form of an adjustment to the threshold values. Two levels of supportive net were studied; one implements an extended additional layer with adjustable neuronal threshold setting mechanism, while the second implements an auxiliary net with traditional architecture performs dynamic adjustment to the threshold value of the main net that is constructed in dual-layer architecture. Experiment results and analysis of the proposed designs have given quite satisfactory conducts. The supportive layer approach achieved over 90% recognition rate, while the multiple network technique shows more effective and acceptable level of recognition. However, this is achieved at the price of network complexity and computation time. Recognition generalization may be also improved by accommodating capabilities involving all the innate structures in conjugation with Intelligence abilities with the needs of further advanced learning phases.
Abstract: Mostly transforms are used for speech data
compressions which are lossy algorithms. Such algorithms are
tolerable for speech data compression since the loss in quality is not
perceived by the human ear. However the vector quantization (VQ)
has a potential to give more data compression maintaining the same
quality. In this paper we propose speech data compression algorithm
using vector quantization technique. We have used VQ algorithms
LBG, KPE and FCG. The results table shows computational
complexity of these three algorithms. Here we have introduced a new
performance parameter Average Fractional Change in Speech
Sample (AFCSS). Our FCG algorithm gives far better performance
considering mean absolute error, AFCSS and complexity as
compared to others.
Abstract: In this paper we propose a simple adaptive algorithm
iteratively solving the unit-norm constrained optimization problem.
Instead of conventional parameter norm based normalization,
the proposed algorithm incorporates scalar normalization which is
computationally much simpler. The analysis of stationary point is
presented to show that the proposed algorithm indeed solves the
constrained optimization problem. The simulation results illustrate
that the proposed algorithm performs as good as conventional ones
while being computationally simpler.
Abstract: In Content-Based Image Retrieval systems it is
important to use an efficient indexing technique in order to perform
and accelerate the search in huge databases. The used indexing
technique should also support the high dimensions of image features.
In this paper we present the hierarchical index NOHIS-tree (Non
Overlapping Hierarchical Index Structure) when we scale up to very
large databases. We also present a study of the influence of clustering
on search time. The performance test results show that NOHIS-tree
performs better than SR-tree. Tests also show that NOHIS-tree keeps
its performances in high dimensional spaces. We include the
performance test that try to determine the number of clusters in
NOHIS-tree to have the best search time.
Abstract: The Mobile IP Standard has been developed to support mobility over the Internet. This standard contains several drawbacks as in the cases where packets are routed via sub-optimal paths and significant amount of signaling messages is generated due to the home registration procedure which keeps the network aware of the current location of the mobile nodes. Recently, a dynamic hierarchical mobility management strategy for mobile IP networks (DHMIP) has been proposed to reduce home registrations costs. However, this strategy induces a packet delivery delay and increases the risk of packet loss. In this paper, we propose an enhanced version of the dynamic hierarchical strategy that reduces the packet delivery delay and minimizes the risk of packet loss. Preliminary results obtained from simulations are promising. They show that the enhanced version outperforms the original dynamic hierarchical mobility management strategy version.
Abstract: Keys to high-quality face-to-face education are ensuring flexibility in the way lectures are given, and providing care and responsiveness to learners. This paper describes a face-to-face education support system that is designed to raise the satisfaction of learners and reduce the workload on instructors. This system consists of a lecture adaptation assistance part, which assists instructors in adapting teaching content and strategy, and a Q&A assistance part, which provides learners with answers to their questions. The core component of the former part is a “learning achievement map", which is composed of a Bayesian network (BN). From learners- performance in exercises on relevant past lectures, the lecture adaptation assistance part obtains information required to adapt appropriately the presentation of the next lecture. The core component of the Q&A assistance part is a case base, which accumulates cases consisting of questions expected from learners and answers to them. The Q&A assistance part is a case-based search system equipped with a search index which performs probabilistic inference. A prototype face-to-face education support system has been built, which is intended for the teaching of Java programming, and this approach was evaluated using this system. The expected degree of understanding of each learner for a future lecture was derived from his or her performance in exercises on past lectures, and this expected degree of understanding was used to select one of three adaptation levels. A model for determining the adaptation level most suitable for the individual learner has been identified. An experimental case base was built to examine the search performance of the Q&A assistance part, and it was found that the rate of successfully finding an appropriate case was 56%.
Abstract: The DNA microarray technology concurrently monitors the expression levels of thousands of genes during significant biological processes and across the related samples. The better understanding of functional genomics is obtained by extracting the patterns hidden in gene expression data. It is handled by clustering which reveals natural structures and identify interesting patterns in the underlying data. In the proposed work clustering gene expression data is done through an Advanced Nelder Mead (ANM) algorithm. Nelder Mead (NM) method is a method designed for optimization process. In Nelder Mead method, the vertices of a triangle are considered as the solutions. Many operations are performed on this triangle to obtain a better result. In the proposed work, the operations like reflection and expansion is eliminated and a new operation called spread-out is introduced. The spread-out operation will increase the global search area and thus provides a better result on optimization. The spread-out operation will give three points and the best among these three points will be used to replace the worst point. The experiment results are analyzed with optimization benchmark test functions and gene expression benchmark datasets. The results show that ANM outperforms NM in both benchmarks.
Abstract: This paper presents the voltage regulation scheme of
D-STATCOM under three-phase faults. It consists of the voltage
detection and voltage regulation schemes in the 0dq reference. The
proposed control strategy uses the proportional controller in which
the proportional gain, kp, is appropriately adjusted by using genetic
algorithms. To verify its use, a simplified 4-bus test system is situated
by assuming a three-phase fault at bus 4. As a result, the DSTATCOM
can resume the load voltage to the desired level within
1.8 ms. This confirms that the proposed voltage regulation scheme
performs well under three-phase fault events.
Abstract: Ants are fascinating creatures that demonstrate the
ability to find food and bring it back to their nest. Their ability as a
colony, to find paths to food sources has inspired the development of
algorithms known as Ant Colony Systems (ACS). The principle of
cooperation forms the backbone of such algorithms, commonly used
to find solutions to problems such as the Traveling Salesman
Problem (TSP). Ants communicate to each other through chemical
substances called pheromones. Modeling individual ants- ability to
manipulate this substance can help an ACS find the best solution.
This paper introduces a Dynamic Ant Colony System with threelevel
updates (DACS3) that enhance an existing ACS. Experiments
were conducted to observe single ant behavior in a colony of
Malaysian House Red Ants. Such behavior was incorporated into the
DACS3 algorithm. We benchmark the performance of DACS3 versus
DACS on TSP instances ranging from 14 to 100 cities. The result
shows that the DACS3 algorithm can achieve shorter distance in
most cases and also performs considerably faster than DACS.
Abstract: The performance of ground to deep space optical
communication systems is degraded by distortion of the beam as it
propagates through the turbulent atmosphere. Turbulence causes
fluctuations in the intensity of the received signal which ultimately
affects the acquisition time required to acquire and locate the spaceborne
target using narrow laser beam. In this paper, performance of
free-space optical (FSO) communication system in atmospheric
turbulence has been analyzed in terms of acquisition time for
coherent and non-coherent modulation schemes. Numerical results
presented in graphical and tabular forms show that the acquisition
time increases with the increase in turbulence level. This is true for
both schemes. The BPSK has lowest acquisition time among all
schemes. In non-coherent schemes, M-PPM performs better than the
other schemes. With the increase in M, acquisition time becomes
lower, but at the cost of increase in system complexity.
Abstract: At present the process of formation of corporate
values in Kazakh universities is under the influence of a whole range
of socio-economic and cultural changes: on the one hand universities
must maintain and transmit traditional cultural values of education,
on the other, to improve quality of service and to involve young
people to science, providing thus own competitiveness. Thus, this
article presents some results of two cycles of sociological research
conducted in 2012 and aimed at identifying possible ways to
popularize science and readiness to participate of youth in given
activities, expectations of young scientists and the prospects of future
development of the Kazakh science.
Abstract: Soft set theory was initiated by Molodtsov in 1999. In the past years, this theory had been applied to many branches of mathematics, information science and computer science. In 2003, Maji et al. introduced some operations of soft sets and gave some operational rules. Recently, some of these operational rules are pointed out to be not true. Furthermore, Ali et al., in their paper, introduced and discussed some new operations of soft sets. In this paper, we further investigate these operational rules given by Maji et al. and Ali et al.. We obtain some sufficient-necessary conditions such that corresponding operational rules hold and give correct forms for some operational rules. These results will be help for us to use rightly operational rules of soft sets in research and application of soft set theory.
Abstract: The strengthening of competitive advantage combined with the transformation of business strategy is necessary for the company to succeed in the time of market changes. And in this sense the innovation activities of the firm are exactly significanting. Virtual firms are a specific form of enterprise in which we can't suppose all regularities obtaining in other forms. The aim of the paper is to evaluate factors influencing the innovation activity of virtual firm with the determination of their importance and influences on the basis of selected metrics.
Abstract: Magnesium wastes are produced by many industrial activities. This waste problem is becoming a future problem for the world. Magnesium borates have many advantages such as; high corrosion resistance, heat resistance, high coefficient of elasticity and can also be used in the production of material against radiation. Addition, magnesium borates have great potential in sectors
including ceramic and detergents industry and superconducting materials.
In this study, using the starting materials of waste magnesium and H3BO3 the hydrothermal method was applied at a moderate
temperature of 70oC. Several mole ratios of waste magnesium to H3BO3 are selected as; 1:2, 1:4, 1:6, 1:8, 1:10. Reaction time was determined as 1 hour. After the synthesis, X-Ray Diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FT-IR) techniques are applied to products. As a result the forms of mcallisterite “Mg2(B6O7(OH)6)2.9(H2O)”, admontite “MgO(B2O3)3.7(H2O)” and magnesium boron hydrate (MgO(B2O3)3.6(H2O)” are obtained.
Abstract: Many problems in computer vision and image
processing present potential for parallel implementations through one
of the three major paradigms of geometric parallelism, algorithmic
parallelism and processor farming. Static process scheduling
techniques are used successfully to exploit geometric and algorithmic
parallelism, while dynamic process scheduling is better suited to
dealing with the independent processes inherent in the process
farming paradigm. This paper considers the application of parallel or
multi-computers to a class of problems exhibiting spatial data
characteristic of the geometric paradigm. However, by using
processor farming paradigm, a dynamic scheduling technique is
developed to suit the MIMD structure of the multi-computers. A
hybrid scheme of scheduling is also developed and compared with
the other schemes. The specific problem chosen for the investigation
is the Hough transform for line detection.
Abstract: Midpoint filter is quite effective in recovering the
images confounded by the short-tailed (uniform) noise. It, however,
performs poorly in the presence of additive long-tailed (impulse)
noise and it does not preserve the edge structures of the image
signals. Median smoother discards outliers (impulses) effectively, but
it fails to provide adequate smoothing for images corrupted with nonimpulse
noise. In this paper, two nonlinear techniques for image
filtering, namely, New Filter I and New Filter II are proposed based
on a nonlinear high-pass filter algorithm. New Filter I is constructed
using a midpoint filter, a highpass filter and a combiner. It suppresses
uniform noise quite well. New Filter II is configured using an alpha
trimmed midpoint filter, a median smoother of window size 3x3, the
high pass filter and the combiner. It is robust against impulse noise
and attenuates uniform noise satisfactorily. Both the filters are shown
to exhibit good response at the image boundaries (edges). The
proposed filters are evaluated for their performance on a test image
and the results obtained are included.
Abstract: Language Reforms and potential use of ICTs has been a focal area of Higher Education Commission of Pakistan. Efforts are being accelerated to incorporate fast expanding ICTs to bring qualitative improvement in language instruction in higher education. This paper explores how university teachers are benefitting from ICTs to make their English class effective and what type of problems they face in practicing ICTs during their lectures. An in-depth qualitative study was employed to understand why language teachers tend to use ICTs in their instruction and how they are practicing it. A sample of twenty teachers from five universities located in Islamabad, three from public sector and two from private sector, was selected on non-random (Snowball) sampling basis. An interview with 15 semi-structured items was used as research instruments to collect data. The findings reveal that business English teaching is facilitated and improved through the use of ICTs. The language teachers need special training regarding the practices and implementation of ICTs. It is recommended that initiatives might be taken to equip university language teachers with modern methodology incorporating ICTs as focal area and efforts might be made to remove barriers regarding the training of language teachers and proper usage of ICTs.