Abstract: The paper shows how the CASMAS modeling language,
and its associated pervasive computing architecture, can be
used to facilitate continuity of care by providing members of patientcentered
communities of care with a support to cooperation and
knowledge sharing through the usage of electronic documents and
digital devices. We consider a scenario of clearly fragmented care to
show how proper mechanisms can be defined to facilitate a better
integration of practices and information across heterogeneous care
networks. The scenario is declined in terms of architectural components
and cooperation-oriented mechanisms that make the support
reactive to the evolution of the context where these communities
operate.
Abstract: An ordered porous antimony-doped tin oxide (ATO) film was successfully prepared using a simple coating process with colloidal templates. The facile production was effective when a combination of 16-nm ATO (as a model of an inorganic nanoparticle) and polystyrene (PS) spheres (as a model of the template) weresimply coated to produce a composite ATO/PS film. Heat treatment was then used to remove the PS and produce the porous film. The porous film with a spherical pore shape and a highly ordered porous structure could be obtained. A potential way for the control of pore size could be also achieved by changing initial template size. The theoretical explanation and mechanism of porous formation were also added, which would be important for the scaling-up prediction and estimation.
Abstract: Nowadays there are many methods for representing
knowledge such as semantic network, neural network, and conceptual
graphs. Nonetheless, these methods are not sufficiently efficient
when applied to perform and deduce on knowledge domains about
supporting in general education such as algebra, analysis or plane
geometry. This leads to the introduction of computational network
which is a useful tool for representation knowledge base, especially
for computational knowledge, especially knowledge domain about
general education. However, when dealing with a practical problem,
we often do not immediately find a new solution, but we search
related problems which have been solved before and then proposing
an appropriate solution for the problem. Besides that, when finding
related problems, we have to determine whether the result of them
can be used to solve the practical problem or not. In this paper, the
extension model of computational network has been presented. In this
model, Sample Problems, which are related problems, will be used
like the experience of human about practical problem, simulate the
way of human thinking, and give the good solution for the practical
problem faster and more effectively. This extension model is applied
to construct an automatic system for solving algebraic problems in
middle school.
Abstract: The compatibility of optical resonators with microfluidic systems may be relevant for chemical and biological applications. Here, a fluorescent-core microcavity (FCM) is investigated as a refractometric sensor for heavy oils. A high-index film of silicon quantum dots (QDs) was formed inside the capillary, supporting cylindrical fluorescence whispering gallery modes (WGMs). A set of standard refractive index oils was injected into a capillary, causing a shift of the WGM resonances toward longer wavelengths. A maximum sensitivity of 240 nm/RIU (refractive index unit) was found for a nominal oil index of 1.74. As well, a sensitivity of 22 nm/RIU was obtained for a lower index of 1.48, more typical of fuel hydrocarbons. Furthermore, the observed spectra and sensitivities were compared to theoretical predictions and reproduced via FDTD simulations, showing in general an excellent agreement. This work demonstrates the potential use of FCMs for oil sensing applications and the more generally for detecting liquid solutions with a high refractive index or high viscosity.
Abstract: Conceptualization strengthens intelligent systems in generalization skill, effective knowledge representation, real-time inference, and managing uncertain and indefinite situations in addition to facilitating knowledge communication for learning agents situated in real world. Concept learning introduces a way of abstraction by which the continuous state is formed as entities called concepts which are connected to the action space and thus, they illustrate somehow the complex action space. Of computational concept learning approaches, action-based conceptualization is favored because of its simplicity and mirror neuron foundations in neuroscience. In this paper, a new biologically inspired concept learning approach based on the probabilistic framework is proposed. This approach exploits and extends the mirror neuron-s role in conceptualization for a reinforcement learning agent in nondeterministic environments. In the proposed method, instead of building a huge numerical knowledge, the concepts are learnt gradually from rewards through interaction with the environment. Moreover the probabilistic formation of the concepts is employed to deal with uncertain and dynamic nature of real problems in addition to the ability of generalization. These characteristics as a whole distinguish the proposed learning algorithm from both a pure classification algorithm and typical reinforcement learning. Simulation results show advantages of the proposed framework in terms of convergence speed as well as generalization and asymptotic behavior because of utilizing both success and failures attempts through received rewards. Experimental results, on the other hand, show the applicability and effectiveness of the proposed method in continuous and noisy environments for a real robotic task such as maze as well as the benefits of implementing an incremental learning scenario in artificial agents.
Abstract: A multi-rate discrete-time model, whose response
agrees exactly with that of a continuous-time original at all sampling
instants for any sampling periods, is developed for a linear system,
which is assumed to have multiple real eigenvalues. The sampling
rates can be chosen arbitrarily and individually, so that their ratios
can even be irrational. The state space model is obtained as a
combination of a linear diagonal state equation and a nonlinear output
equation. Unlike the usual lifted model, the order of the proposed
model is the same as the number of sampling rates, which is less than
or equal to the order of the original continuous-time system. The
method is based on a nonlinear variable transformation, which can be
considered as a generalization of linear similarity transformation,
which cannot be applied to systems with multiple eigenvalues in
general. An example and its simulation result show that the proposed
multi-rate model gives exact responses at all sampling instants.
Abstract: This paper describes a novel approach for deriving
modules from protein-protein interaction networks, which combines
functional information with topological properties of the network.
This approach is based on weighted clustering coefficient, which
uses weights representing the functional similarities between the
proteins. These weights are calculated according to the semantic
similarity between the proteins, which is based on their Gene
Ontology terms. We recently proposed an algorithm for identification
of functional modules, called SWEMODE (Semantic WEights for
MODule Elucidation), that identifies dense sub-graphs containing
functionally similar proteins. The rational underlying this approach is
that each module can be reduced to a set of triangles (protein triplets
connected to each other). Here, we propose considering semantic
similarity weights of all triangle-forming edges between proteins. We
also apply varying semantic similarity thresholds between
neighbours of each node that are not neighbours to each other (and
hereby do not form a triangle), to derive new potential triangles to
include in module-defining procedure. The results show an
improvement of pure topological approach, in terms of number of
predicted modules that match known complexes.
Abstract: Performance of any continuous speech recognition system is highly dependent on performance of the acoustic models. Generally, development of the robust spoken language technology relies on the availability of large amounts of data. Common way to cope with little data for training each state of Markov models is treebased state tying. This tying method applies contextual questions to tie states. Manual procedure for question generation suffers from human errors and is time consuming. Various automatically generated questions are used to construct decision tree. There are three approaches to generate questions to construct HMMs based on decision tree. One approach is based on misrecognized phonemes, another approach basically uses feature table and the other is based on state distributions corresponding to context-independent subword units. In this paper, all these methods of automatic question generation are applied to the decision tree on FARSDAT corpus in Persian language and their results are compared with those of manually generated questions. The results show that automatically generated questions yield much better results and can replace manually generated questions in Persian language.
Abstract: Regenerative gas turbine engine cycle is presented that yields higher cycle efficiencies than simple cycle operating under the same conditions. The power output, efficiency and specific fuel consumption are simulated with respect to operating conditions. The analytical formulae about the relation to determine the thermal efficiency are derived taking into account the effected operation conditions (ambient temperature, compression ratio, regenerator effectiveness, compressor efficiency, turbine efficiency and turbine inlet temperature). Model calculations for a wide range of parameters are presented, as are comparisons with simple gas turbine cycle. The power output and thermal efficiency are found to be increasing with the regenerative effectiveness, and the compressor and turbine efficiencies. The efficiency increased with increase the compression ratio to 5, then efficiency decreased with increased compression ratio, but in simple cycle the thermal efficiency always increase with increased in compression ratio. The increased in ambient temperature caused decreased thermal efficiency, but the increased in turbine inlet temperature increase thermal efficiency.
Abstract: Developers need to evaluate software's performance to make software efficient. This paper suggests a performance evaluation system for embedded software. The suggested system consists of code analyzer, testing agents, data analyzer, and report viewer. The code analyzer inserts additional code dependent on target system into source code and compiles the source code. The testing agents execute performance test. The data analyzer translates raw-level results data to class-level APIs for reporting viewer. The report viewer offers users graphical report views by using the APIs. We hope that the suggested tool will be useful for embedded-related software development,because developers can easily and intuitively analyze software's performance and resource utilization.
Abstract: In this paper, we intend to study the synthesis of the
multibeam arrays. The synthesis implementation-s method for this
type of arrays permits to approach the appropriated radiance-s
diagram. The used approach is based on neural network that are
capable to model the multibeam arrays, consider predetermined
general criteria-s, and finally it permits to predict the appropriated
diagram from the neural model. Our main contribution in this paper is
the extension of a synthesis model of these multibeam arrays.
Abstract: Silver/polylactide nanocomposites (Ag/PLA-NCs) were
synthesized via chemical reduction method in diphase solvent. Silver
nitrate and sodium borohydride were used as a silver precursor
and reducing agent in the polylactide (PLA). The properties of
Ag/PLA-NCs were studied as a function of the weight percentages
of silver nanoparticles (8, 16 and 32 wt% of Ag-NPs) relative to
the weight of PLA. The Ag/PLA-NCs were characterized by Xray
diffraction (XRD), transmission electron microscopy (TEM),
electro-optical microscopy (EOM), UV-visible spectroscopy (UV-vis)
and Fourier transform infrared spectroscopy (FT-IR). XRD patterns
confirmed that Ag-NPs crystallographic planes were face centered
cubic (fcc) type. TEM images showed that mean diameters of Ag-NPs
were 3.30, 3.80 and 4.80 nm. Electro-optical microscopy revealed
excellent dispersion and interaction between Ag-NPs and PLA films.
The generation of silver nanoparticles was confirmed from the UVvisible
spectra. FT-IR spectra showed that there were no significant
differences between PLA and Ag/PLA-NCs films. The synthesized
Ag/PLA-NCs were stable in organic solution over a long period of
time without sign of precipitation.
Abstract: In the paper, the energetic features of the loaded gait
are newly analyzed depending on the trunk flexion change. To
investigate the loaded gait, walking experiments are performed for five
subjects and, the ground reaction forces and kinematic data are
measured. Based on these information, we compute the impulse,
momentum and mechanical works done on the center of body mass,
through the trunk flexion change. As a result, it is shown that the trunk
flexion change does not affect the impulses and momentums during
the step-to-step transition as well. However, the direction of the
pre-collision momentum does change depending on the trunk flexion
change, which is degenerated just after (or during) the collision period.
Abstract: This paper explores the opportunity of using tri-axial
wireless accelerometers for supervised monitoring of sports
movements. A motion analysis system for the upper extremities of
lawn bowlers in particular is developed. Accelerometers are placed
on parts of human body such as the chest to represent the shoulder
movements, the back to capture the trunk motion, back of the hand,
the wrist and one above the elbow, to capture arm movements. These
sensors placement are carefully designed in order to avoid restricting
bowler-s movements. Data is acquired from these sensors in soft-real
time using virtual instrumentation; the acquired data is then
conditioned and converted into required parameters for motion
regeneration. A user interface was also created to facilitate in the
acquisition of data, and broadcasting of commands to the wireless
accelerometers. All motion regeneration in this paper deals with the
motion of the human body segment in the X and Y direction, looking
into the motion of the anterior/ posterior and lateral directions
respectively.
Abstract: Genetically modified (GM) technology in food
production continued to generate controversies. Consumers were
concerned with the GM foods about the healthy and environmental
risks. While consumers- acceptance was a critical factor affecting how
widely this technology be used. According to the research review,
consumers- lack of information was one of the reasons to explain
consumers- low acceptance toward GM foods. The objective for this
study wanted to find out would informative product package affect
consumers- behavior toward GM foods. An experiment was designed
to investigate consumer behavior toward different product package
information. The results indicated that the product package
information influenced consumer product trust toward GM foods.
Compared with the traceability production system information, the
information about the GM rice was approved by authorized
organizations could increase consumers product trust in GM foods.
Consumers in Taiwan saw the information provided by authorized
organizations more credible than other information.
Abstract: We report a novel fusion tag for expressing
recombinant proteins in E. coli. The fusion tag is the C-terminus part
of the human GMCSF gene comprising 45 amino acids, which aid in
over expression of otherwise non expressible genes. Expression of
hIFN a2b with this fusion tag also escapes the requirement of rare
codons for expression. This is also a first report of a small fusion tag
of human origin having affinity to heparin sepharose column
facilitating the purification of fusion protein.
Abstract: A new dynamic clustering approach (DCPSO), based
on Particle Swarm Optimization, is proposed. This approach is
applied to unsupervised image classification. The proposed approach
automatically determines the "optimum" number of clusters and
simultaneously clusters the data set with minimal user interference.
The algorithm starts by partitioning the data set into a relatively large
number of clusters to reduce the effects of initial conditions. Using
binary particle swarm optimization the "best" number of clusters is
selected. The centers of the chosen clusters is then refined via the Kmeans
clustering algorithm. The experiments conducted show that
the proposed approach generally found the "optimum" number of
clusters on the tested images.
Abstract: This paper represents four unsupervised clustering algorithms namely sIB, RandomFlatClustering, FarthestFirst, and FilteredClusterer that previously works have not been used for network traffic classification. The methodology, the result, the products of the cluster and evaluation of these algorithms with efficiency of each algorithm from accuracy are shown. Otherwise, the efficiency of these algorithms considering form the time that it use to generate the cluster quickly and correctly. Our work study and test the best algorithm by using classify traffic anomaly in network traffic with different attribute that have not been used before. We analyses the algorithm that have the best efficiency or the best learning and compare it to the previously used (K-Means). Our research will be use to develop anomaly detection system to more efficiency and more require in the future.
Abstract: Rice husk is a lignocellulosic source that can be
converted to ethanol. Three hundreds grams of rice husk was mixed
with 1 L of 0.18 N sulfuric acid solutions then was heated in an
autoclave. The reaction was expected to be at constant temperature
(isothermal), but before that temperature was achieved, reaction has
occurred. The first liquid sample was taken at temperature of 140 0C
and repeated every 5 minute interval. So the data obtained are in the
regions of non-isothermal and isothermal. It was observed that the
degradation has significant effects on the ethanol production. The
kinetic constants can be expressed by Arrhenius equation with the
frequency factors for hydrolysis and sugar degradation of 1.58 x 105
1/min and 2.29 x 108 L/mole/min, respectively, while the activation
energies are 64,350 J/mole and 76,571 J/mole. The highest ethanol
concentration from fermentation is 1.13% v/v, attained at 220 0C.
Abstract: This paper focuses on assessment of air pollution in Umm-Alhyman, Kuwait, which is located south to oil refineries, power station, oil field, and highways. The measurements were made over a period of four days in March and July in 2001, 2004, and 2008. The measured pollutants included methanated and nonmethanated hydrocarbons (MHC, NMHC), CO, CO2, SO2, NOX, O3, and PM10. Also, meteorological parameters were measured, which includes temperature, wind speed and direction, and solar radiation. Over the study period, data analysis showed increase in measured SO2, NOX and CO by factors of 1.2, 5.5 and 2, respectively. This is explained in terms of increase in industrial activities, motor vehicle density, and power generation. Predictions of the measured data were made by the ISC-AERMOD software package and by using the ISCST3 model option. Finally, comparison was made between measured data against international standards.