Abstract: A multimedia presentation system refers to the integration of a multimedia database with a presentation manager which has the functionality of content selection, organization and playout of multimedia presentations. It requires high performance of involved system components. Starting from multimedia information capture until the presentation delivery, high performance tools are required for accessing, manipulating, storing and retrieving these segments, for transferring and delivering them in a presentation terminal according to a playout order. The organization of presentations is a complex task in that the display order of presentation contents (in time and space) must be specified. A multimedia presentation contains audio, video, images and text media types. The critical decisions for presentation construction include what the contents are, how the contents are organized, and once the decision is made on the organization of the contents of the presentation, it must be conveyed to the end user in the correct organizational order and in a timely fashion. This paper introduces a framework for specification of multimedia presentations and describes the design of sample presentations using this framework from a multimedia database.
Abstract: High power laser – total emissivity method (HPL-TE method) for determination of coatings relative total emissivity dependent on the temperature is introduced. Method principle, experimental and evaluation parts of the method are described. Computer model of HPL-TE method is employed to perform the sensitivity analysis of the effect of method parameters on the sample surface temperature in the positions where the surface temperature and radiation heat flux are measured.
Abstract: The aim of this paper is to exhibit some properties of
local topologies of an IVS. Also, we Introduce ISG structure as an
interesting structure of semigroups in IVSs.
Abstract: This work describes a CACSD tool for automatic design of robust controllers for hydraulic turbines. The tool calculates the optimal controller using the MATLAB hinfopt function and it
serves as a practical and effective solution for the laborious task of
designing a different controller for each type of turbine and generator, and different parameters and conditions of the plant. Results of the simulation of a generating unit subject to parameters
variation show the accuracy and efficiency of the obtained robust
controllers.
Abstract: A kind of behavior model for discrete sampling and hold amplifier with charge transmission is analyzed. The transfer function and behavior features are based on the main AC responses of operation amplifier. The result used in pipelined and sigma-delta ADC shows the exact of model of sampling and hold amplifier, and the non-ideal factors are taken into account.
Abstract: Present study summarizes the control of Vibrio
alginolyticus infection in hatchery reared Clownfish, Amphiprion
sebae with the extract of the mangrove plant, Avicennia marina.
Fishes with visible symptoms of hemorrhagic spots were chosen and
the genomic DNA of the causative bacterium was isolated and
sequenced based on 16S rDNA gene. The in vitro assay revealed that
a fraction of A. marina leaf extract elucidated with ethyl acetate:
methanol (6:4) showed a high activity (28 mm) at 125 μg/ml
concentrations. About 4 % of the fraction fed along with live V.
alginolyticus was significantly decreased the cumulative mortality
(P
Abstract: This paper examines the problem of designing a robust H∞ filter for a class of uncertain fuzzy descriptor systems described by a Takagi-Sugeno (TS) fuzzy model. Based on a linear matrix inequality (LMI) approach, LMI-based sufficient conditions for the uncertain nonlinear descriptor systems to have an H∞ performance are derived. To alleviate the ill-conditioning resulting from the interaction of slow and fast dynamic modes, solutions to the problem are given in terms of linear matrix inequalities which are independent of the singular perturbation ε, when ε is sufficiently small. The proposed approach does not involve the separation of states into slow and fast ones and it can be applied not only to standard, but also to nonstandard uncertain nonlinear descriptor systems. A numerical example is provided to illustrate the design developed in this paper.
Abstract: recurrent neural network (RNN) is an efficient tool for
modeling production control process as well as modeling services. In
this paper one RNN was combined with regression model and were
employed in order to be checked whether the obtained data by the
model in comparison with actual data, are valid for variable process
control chart. Therefore, one maintenance process in workshop of
Esfahan Oil Refining Co. (EORC) was taken for illustration of
models. First, the regression was made for predicting the response
time of process based upon determined factors, and then the error
between actual and predicted response time as output and also the
same factors as input were used in RNN. Finally, according to
predicted data from combined model, it is scrutinized for test values
in statistical process control whether forecasting efficiency is
acceptable. Meanwhile, in training process of RNN, design of
experiments was set so as to optimize the RNN.
Abstract: This paper describes a combined mathematicalgraphical
approach for optimum tool path planning in order to
improve machining efficiency. A methodology has been used that
stabilizes machining operations by adjusting material removal rate in
pocket milling operations while keeping cutting forces within limits.
This increases the life of cutting tool and reduces the risk of tool
breakage, machining vibration, and chatter. Case studies reveal the
fact that application of this approach could result in a slight increase
of machining time, however, a considerable reduction of tooling cost,
machining vibration, noise and chatter can be achieved in addition to
producing a better surface finish.
Abstract: Early detection of breast cancer is considered as a
major public health issue. Breast cancer screening is not generalized
to the entire population due to a lack of resources, staff and
appropriate tools. Systematic screening can result in a volume of data
which can not be managed by present computer architecture, either in
terms of storage capabilities or in terms of exploitation tools. We
propose in this paper to design and develop a data warehouse system
in radiology-senology (DWRS). The aim of such a system is on one
hand, to support this important volume of information providing from
multiple sources of data and images and for the other hand, to help
assist breast cancer screening in diagnosis, education and research.
Abstract: There is a world-wide need for the development of sustainable management strategies to control pest infestation and the development of phosphine (PH3) resistance in lesser grain borer (Rhyzopertha dominica). Computer simulation models can provide a relatively fast, safe and inexpensive way to weigh the merits of various management options. However, the usefulness of simulation models relies on the accurate estimation of important model parameters, such as mortality. Concentration and time of exposure are both important in determining mortality in response to a toxic agent. Recent research indicated the existence of two resistance phenotypes in R. dominica in Australia, weak and strong, and revealed that the presence of resistance alleles at two loci confers strong resistance, thus motivating the construction of a two-locus model of resistance. Experimental data sets on purified pest strains, each corresponding to a single genotype of our two-locus model, were also available. Hence it became possible to explicitly include mortalities of the different genotypes in the model. In this paper we described how we used two generalized linear models (GLM), probit and logistic models, to fit the available experimental data sets. We used a direct algebraic approach generalized inverse matrix technique, rather than the traditional maximum likelihood estimation, to estimate the model parameters. The results show that both probit and logistic models fit the data sets well but the former is much better in terms of small least squares (numerical) errors. Meanwhile, the generalized inverse matrix technique achieved similar accuracy results to those from the maximum likelihood estimation, but is less time consuming and computationally demanding.
Abstract: The present report describes the characteristics of
damages and behavior of reinforced concrete buildings during the
tsunami action. The discussion is based on the field damage survey in
selected cities located on the coast of the zone affected by the Great
East Japan Earthquake on March 11, 2011. This earthquake is the most
powerful know earthquake that has hit Japan with a magnitude 9.0 and
with epicenter located at 129 km of Sendai city (off the coast). The
earthquake triggered a destructive tsunami with run up height of up to
40 meters that mainly affect cities located on the Pacific Ocean coast of
the Tohoku region (north-east region of Japan). Reinforced concrete
buildings in general resist the tsunami without collapse however the
non-structural elements like panels and ceilings were severely
damaged. The analysis of damages has permitted to understand the
behavior of RC buildings under tsunami attack, and has also permitted
to establish recommendations for their use to take refuge from tsunami
in places where natural topography makes impossible to reach hilltops
or other safer places.
Abstract: Recently many research has been conducted to
retrieve pertinent parameters and adequate models for automatic
music genre classification. In this paper, two measures based upon
information theory concepts are investigated for mapping the features
space to decision space. A Gaussian Mixture Model (GMM) is used
as a baseline and reference system. Various strategies are proposed
for training and testing sessions with matched or mismatched
conditions, long training and long testing, long training and short
testing. For all experiments, the file sections used for testing are
never been used during training. With matched conditions all
examined measures yield the best and similar scores (almost 100%).
With mismatched conditions, the proposed measures yield better
scores than the GMM baseline system, especially for the short testing
case. It is also observed that the average discrimination information
measure is most appropriate for music category classifications and on
the other hand the divergence measure is more suitable for music
subcategory classifications.
Abstract: The scroll pump belongs to the category of positive
displacement pump can be used for continuous pumping of gases at
low pressure apart from general vacuum application. The shape of
volume occupied by the gas moves and deforms continuously as the
spiral orbits. To capture flow features in such domain where mesh
deformation varies with time in a complicated manner, mesh less
solver was found to be very useful. Least Squares Kinetic Upwind
Method (LSKUM) is a kinetic theory based mesh free Euler solver
working on arbitrary distribution of points. Here upwind is enforced
in molecular level based on kinetic flux vector splitting scheme
(KFVS). In the present study we extended the LSKUM to moving
node viscous flow application. This new code LSKUM-NS-MN for
moving node viscous flow is validated for standard airfoil pitching
test case. Simulation performed for flow through scroll pump using
LSKUM-NS-MN code agrees well with the experimental pumping
speed data.
Abstract: Modeling the behavior of the dialogue management in
the design of a spoken dialogue system using statistical methodologies
is currently a growing research area. This paper presents a work
on developing an adaptive learning approach to optimize dialogue
strategy. At the core of our system is a method formalizing dialogue
management as a sequential decision making under uncertainty whose
underlying probabilistic structure has a Markov Chain. Researchers
have mostly focused on model-free algorithms for automating the
design of dialogue management using machine learning techniques
such as reinforcement learning. But in model-free algorithms there
exist a dilemma in engaging the type of exploration versus exploitation.
Hence we present a model-based online policy learning
algorithm using interconnected learning automata for optimizing
dialogue strategy. The proposed algorithm is capable of deriving
an optimal policy that prescribes what action should be taken in
various states of conversation so as to maximize the expected total
reward to attain the goal and incorporates good exploration and
exploitation in its updates to improve the naturalness of humancomputer
interaction. We test the proposed approach using the most
sophisticated evaluation framework PARADISE for accessing to the
railway information system.
Abstract: This paper describes interconnection between
technical and economical making decision. The reason of this dealing
could be different: poor technical condition, change of substation
(electrical network) regime, power transformer owner budget deficit
and increasing of tariff on electricity. Establishing of recommended
practice as well as to give general advice and guidance in economical
sector, testing, diagnostic power transformers to establish its
conditions, identify problems and provide potential remedies.
Abstract: The physiological effects of physical exercise on
human body are relatively well known in literature, which describes
in detail the changes that occur in the cardiovascular system, the
respiratory one, in bones and other systems, both during exercise
and after its delivery. However, the effects of exercise on mental
processes are less treated. From the literature reviews discussed in
this study, it can be detached the idea that we can not exactly say that
physical exercise has beneficial effects on mental processes, but
neither that it would have potentially negative effects. This
uncertainty, reflected in the inability to indicate precise and
unequivocal meaning, favorable-unfavorable physical effort in acting
on mental processes, is a prime reason to undertake a study of the
phenomenon influence effort administered physical education classes
on the dynamics of mental processes like attention and memory.
Abstract: In recent years, an increased competition and lower profit margins have necessitated a focus on improving the performance of the product development process, an area that traditionally have been excluded from detailed steering and evaluation. A systematic improvement requires a good understanding of the current performance, wherefore the interest for product development performance measurement has increased dramatically. This paper presents a case study that evaluates the performance of the product development performance measurement system used in a Swedish company that is a part of a global corporate group. The study is based on internal documentation and eighteen in-depth interviews with stakeholders involved in the product development process. The results from the case study includes a description of what metrics that are in use, how these are employed, and its affect on the quality of the performance measurement system. Especially, the importance of having a well-defined process proved to have a major impact on the quality of the performance measurement system in this particular case.
Abstract: Mobiles are considered to be the most frequently used
electronic items in world after electricity. It is probably the only
device that can be used by any gender with no age limits depending
on its functionality. This paper present the interactive interface of
Mobile and particularly aiming the use of advanced phones which are
also called smart phones. With the changes in the trend where users
are now moving from ordinary mobiles to the one with touch screens
and facilities such as WiFi and internet browsing.
Abstract: In the context of spectrum surveillance, a new method
to recover the code of spread spectrum signal is presented, while the
receiver has no knowledge of the transmitter-s spreading sequence. In
our previous paper, we used Genetic algorithm (GA), to recover
spreading code. Although genetic algorithms (GAs) are well known
for their robustness in solving complex optimization problems, but
nonetheless, by increasing the length of the code, we will often lead
to an unacceptable slow convergence speed. To solve this problem we
introduce Particle Swarm Optimization (PSO) into code estimation in
spread spectrum communication system. In searching process for
code estimation, the PSO algorithm has the merits of rapid
convergence to the global optimum, without being trapped in local
suboptimum, and good robustness to noise. In this paper we describe
how to implement PSO as a component of a searching algorithm in
code estimation. Swarm intelligence boasts a number of advantages
due to the use of mobile agents. Some of them are: Scalability, Fault
tolerance, Adaptation, Speed, Modularity, Autonomy, and
Parallelism. These properties make swarm intelligence very attractive
for spread spectrum code estimation. They also make swarm
intelligence suitable for a variety of other kinds of channels. Our
results compare between swarm-based algorithms and Genetic
algorithms, and also show PSO algorithm performance in code
estimation process.