Abstract: The Internet is the global data communications
infrastructure based on the interconnection of both public and private
networks using protocols that implement Internetworking on a global
scale. Hence the control of protocol and infrastructure development,
resource allocation and network operation are crucial and interlinked
aspects. Internet Governance is the hotly debated and contentious
subject that refers to the global control and operation of key Internet
infrastructure such as domain name servers and resources such as
domain names. It is impossible to separate technical and political
positions as they are interlinked. Furthermore the existence of a
global market, transparency and competition impact upon Internet
Governance and related topics such as network neutrality and
security. Current trends and developments regarding Internet
governance with a focus on the policy-making process, security and
control have been observed to evaluate current and future
implications on the Internet. The multi stakeholder approach to
Internet Governance discussed in this paper presents a number of
opportunities, issues and developments that will affect the future
direction of the Internet. Internet operation, maintenance and
advisory organisations such as the Internet Corporation for Assigned
Names and Numbers (ICANN) or the Internet Governance Forum
(IGF) are currently in the process of formulating policies for future
Internet Governance. Given the controversial nature of the issues at
stake and the current lack of agreement it is predicted that
institutional as well as market governance will remain present for the
network access and content.
Abstract: To evaluate the ability to predict xerostomia after
radiotherapy, we constructed and compared neural network and
logistic regression models. In this study, 61 patients who completed a
questionnaire about their quality of life (QoL) before and after a full
course of radiation therapy were included. Based on this questionnaire,
some statistical data about the condition of the patients’ salivary
glands were obtained, and these subjects were included as the inputs of
the neural network and logistic regression models in order to predict
the probability of xerostomia. Seven variables were then selected from
the statistical data according to Cramer’s V and point-biserial
correlation values and were trained by each model to obtain the
respective outputs which were 0.88 and 0.89 for AUC, 9.20 and 7.65
for SSE, and 13.7% and 19.0% for MAPE, respectively. These
parameters demonstrate that both neural network and logistic
regression methods are effective for predicting conditions of parotid
glands.
Abstract: This study demonstrates the use of Class F fly ash in
combination with lime or lime kiln dust in the full depth reclamation
(FDR) of asphalt pavements. FDR, in the context of this paper, is a
process of pulverizing a predetermined amount of flexible pavement
that is structurally deficient, blending it with chemical additives and
water, and compacting it in place to construct a new stabilized base
course. Test sections of two structurally deficient asphalt pavements
were reclaimed using Class F fly ash in combination with lime and
lime kiln dust. In addition, control sections were constructed using
cement, cement and emulsion, lime kiln dust and emulsion, and mill
and fill. The service performance and structural behavior of the FDR
pavement test sections were monitored to determine how the fly ash
sections compared to other more traditional pavement rehabilitation
techniques. Service performance and structural behavior were
determined with the use of sensors embedded in the road and Falling
Weight Deflectometer (FWD) tests. Monitoring results of the FWD
tests conducted up to 2 years after reclamation show that the cement,
fly ash+LKD, and fly ash+lime sections exhibited two year resilient
modulus values comparable to open graded cement stabilized
aggregates (more than 750 ksi). The cement treatment resulted in a
significant increase in resilient modulus within 3 weeks of
construction and beyond this curing time, the stiffness increase was
slow. On the other hand, the fly ash+LKD and fly ash+lime test
sections indicated slower shorter-term increase in stiffness. The fly
ash+LKD and fly ash+lime section average resilient modulus values
at two years after construction were in excess of 800 ksi. Additional
longer-term testing data will be available from ongoing pavement
performance and environmental condition data collection at the two
pavement sites.
Abstract: Experimental data are presented to show the influence of different types of chemical demulsifier on the stability and demulsification of emulsions. Three groups of demulsifier with different functional groups were used in this work namely amines, alcohol and polyhydric alcohol. The results obtained in this study have exposed the capability of chemical breaking agents in destabilization of water in crude oil emulsions. From the present study, found that molecular weight of the demulsifier were influent the capability of the emulsion to separate.
Abstract: Fructooligosaccharides derived from microbial enzyme especially from fungal sources has been received particular attention due to its beneficial effects as prebiotics and mass production. However, fungal fermentation is always cumbersome due to its broth rheology problem that will eventually affect the production of FOS. This study investigated the efficiency of immobilized cell system using rotating fibrous bed bioreactor (RFBB) in producing fructooligosaccharides (FOS). A comparative picture with respect to conventional stirred tank bioreactor (CSTB) and RFBB has been presented. To demonstrate the effect of agitation intensity and aeration rate, a laboratory-scale bioreactor 2.5 L was operated in three phases (high, medium, low) for 48 hours. Agitation speed has a great influence on P. simplicissimum fermentation for FOS production, where the volumetric FOS productivity using RFBB is increased with almost 4 fold compared to the FOS productivity in CSTB that only 0.319 g/L/h. Rate of FOS production increased up to 1.2 fold when immobilized cells system was employed at aeration rate similar to the freely suspended cells at 2.0 vvm.
Abstract: Current research has explored the impact of
instructional immediacy, defined as those behaviors that help build
close relationships or feelings of closeness, both on cognition and
motivation in the traditional classroom and online classroom;
however, online courses continue to suffer from higher dropout rates.
Based on Albert Bandura-s Social Cognitive Theory, four primary
relationships or interactions in an online course will be explored in
light of how they can provide immediacy thereby reducing student
attrition and improving cognitive learning. The four relationships are
teacher-student, student-student, and student-content, and studentcomputer.
Results of a study conducted with inservice teachers
completing a 14-week online professional development technology
course will be examined to demonstrate immediacy strategies that
improve cognitive learning and reduce student attrition. Results of
the study reveal that students can be motivated through various
interactions and instructional immediacy behaviors which lead to
higher completion rates, improved self-efficacy, and cognitive
learning.
Abstract: Nanostructured Iron Oxide with different
morphologies of rod-like and granular have been suc-cessfully
prepared via a solid-state reaction in the presence of NaCl, NaBr, NaI
and NaN3, respectively. The added salts not only prevent a drastic
increase in the size of the products but also provide suitable
conditions for the oriented growth of primary nanoparticles. The
formation mechanisms of these materials by solid-state reaction at
ambient temperature are proposed. The photocatalytic experiments
for congo red (CR) have demonstrated that the mixture of α-Fe2O3
and Fe3O4 nanostructures were more efficient than α-Fe2O3
nanostructures.
Abstract: As nanotechnology advances, the use of nanotechnology for medical purposes in the field of nanomedicine seems more promising; the rise of nanorobots for medical diagnostics and treatments could be arriving in the near future. This study proposes a swarm intelligence based control mechanism for swarm nanorobots that operate as artificial platelets to search for wounds. The canonical particle swarm optimization algorithm is employed in this study. A simulation in the circulatory system is constructed and used for demonstrating the movement of nanorobots with essential characteristics to examine the performance of proposed control mechanism. The effects of three nanorobot capabilities including their perception range, maximum velocity and respond time are investigated. The results show that canonical particle swarm optimization can be used to control the early version nanorobots with simple behaviors and actions.
Abstract: The present models and simulation algorithms of intracellular stochastic kinetics are usually based on the premise that diffusion is so fast that the concentrations of all the involved species are homogeneous in space. However, recents experimental measurements of intracellular diffusion constants indicate that the assumption of a homogeneous well-stirred cytosol is not necessarily valid even for small prokaryotic cells. In this work a mathematical treatment of diffusion that can be incorporated in a stochastic algorithm simulating the dynamics of a reaction-diffusion system is presented. The movement of a molecule A from a region i to a region j of the space is represented as a first order reaction Ai k- ! Aj , where the rate constant k depends on the diffusion coefficient. The diffusion coefficients are modeled as function of the local concentration of the solutes, their intrinsic viscosities, their frictional coefficients and the temperature of the system. The stochastic time evolution of the system is given by the occurrence of diffusion events and chemical reaction events. At each time step an event (reaction or diffusion) is selected from a probability distribution of waiting times determined by the intrinsic reaction kinetics and diffusion dynamics. To demonstrate the method the simulation results of the reaction-diffusion system of chaperoneassisted protein folding in cytoplasm are shown.
Abstract: Deep and radical social reforms of the last century-s
nineties in many Eastern European countries caused changes in
Information Technology-s (IT) field. Inefficient information
technologies were rapidly replaced with forefront IT solutions, e.g.,
in Eastern European countries there is a high level penetration of
qualitative high-speed Internet. The authors have taken part in the
introduction of those changes in Latvia-s leading IT research
institute. Grounding on their experience authors in this paper offer an
IT services based model for analysis the mentioned changes- and
development processes in the higher education and research fields,
i.e., for research e-infrastructure-s development. Compare to the
international practice such services were developed in Eastern Europe
in an untraditional way, which provided swift and positive
technological changes.
Abstract: Sputum smear conversion after one month of antituberculosis
therapy in new smear positive pulmonary tuberculosis
patients (PTB+) is a vital indicator towards treatment success. The
objective of this study is to determine the rate of sputum smear
conversion in new PTB+ patients after one month under treatment of
National Institute of Diseases of the Chest and Hospital (NIDCH).
Analysis of sputum smear conversion was done by re-clinical
examination with sputum smear microscopic test after one month.
Socio-demographic and hematological parameters were evaluated to
perceive the correlation with the disease status. Among all enrolled
patients only 33.33% were available for follow up diagnosis and of
them only 42.86% patients turned to smear negative. Probably this
consequence is due to non-coherence to the proper disease
management. 66.67% and 78.78% patients reported low haemoglobin
and packed cell volume level respectively whereas 80% and 93.33%
patients accounted accelerated platelet count and erythrocyte
sedimentation rate correspondingly.
Abstract: Evolutionary Algorithms are population-based,
stochastic search techniques, widely used as efficient global
optimizers. However, many real life optimization problems often
require finding optimal solution to complex high dimensional,
multimodal problems involving computationally very expensive
fitness function evaluations. Use of evolutionary algorithms in such
problem domains is thus practically prohibitive. An attractive
alternative is to build meta models or use an approximation of the
actual fitness functions to be evaluated. These meta models are order
of magnitude cheaper to evaluate compared to the actual function
evaluation. Many regression and interpolation tools are available to
build such meta models. This paper briefly discusses the
architectures and use of such meta-modeling tools in an evolutionary
optimization context. We further present two evolutionary algorithm
frameworks which involve use of meta models for fitness function
evaluation. The first framework, namely the Dynamic Approximate
Fitness based Hybrid EA (DAFHEA) model [14] reduces
computation time by controlled use of meta-models (in this case
approximate model generated by Support Vector Machine
regression) to partially replace the actual function evaluation by
approximate function evaluation. However, the underlying
assumption in DAFHEA is that the training samples for the metamodel
are generated from a single uniform model. This does not take
into account uncertain scenarios involving noisy fitness functions.
The second model, DAFHEA-II, an enhanced version of the original
DAFHEA framework, incorporates a multiple-model based learning
approach for the support vector machine approximator to handle
noisy functions [15]. Empirical results obtained by evaluating the
frameworks using several benchmark functions demonstrate their
efficiency
Abstract: This conference paper discusses a risk allocation problem for subprime investing banks involving investment in subprime structured mortgage products (SMPs) and Treasuries. In order to solve this problem, we develop a L'evy process-based model of jump diffusion-type for investment choice in subprime SMPs and Treasuries. This model incorporates subprime SMP losses for which credit default insurance in the form of credit default swaps (CDSs) can be purchased. In essence, we solve a mean swap-at-risk (SaR) optimization problem for investment which determines optimal allocation between SMPs and Treasuries subject to credit risk protection via CDSs. In this regard, SaR is indicative of how much protection investors must purchase from swap protection sellers in order to cover possible losses from SMP default. Here, SaR is defined in terms of value-at-risk (VaR). Finally, we provide an analysis of the aforementioned optimization problem and its connections with the subprime mortgage crisis (SMC).
Abstract: The conjugate gradient optimization algorithm
usually used for nonlinear least squares is presented and is
combined with the modified back propagation algorithm yielding
a new fast training multilayer perceptron (MLP) algorithm
(CGFR/AG). The approaches presented in the paper consist of
three steps: (1) Modification on standard back propagation
algorithm by introducing gain variation term of the activation
function, (2) Calculating the gradient descent on error with
respect to the weights and gains values and (3) the determination
of the new search direction by exploiting the information
calculated by gradient descent in step (2) as well as the previous
search direction. The proposed method improved the training
efficiency of back propagation algorithm by adaptively modifying
the initial search direction. Performance of the proposed method
is demonstrated by comparing to the conjugate gradient algorithm
from neural network toolbox for the chosen benchmark. The
results show that the number of iterations required by the
proposed method to converge is less than 20% of what is required
by the standard conjugate gradient and neural network toolbox
algorithm.
Abstract: This paper deals with the conceptual design of the
new aeroelastic demonstrator for the whirl flutter simulation. The
paper gives a theoretical background of the whirl flutter phenomenon
and describes the events of the whirl flutter occurrence in the
aerospace practice. The second part is focused on the experimental
research of the whirl flutter on aeroelastic similar models. Finally the
concept of the new aeroelastic demonstrator is described. The
demonstrator represents the wing and engine of the twin turboprop
commuter aircraft including a driven propeller. It allows the changes
of the main structural parameters influencing the whirl flutter
stability characteristics. It is intended for the experimental
investigation of the whirl flutter in the wind tunnel. The results will
be utilized for validation of analytical methods and software tools.
Abstract: This article discusses the customs and traditions in
Turkestan in the late XIXth and early XXth centuries. Having a long
history, Turkestan is well-known as the birthplace of many nations
and nationalities. The name of Turkestan is also given to it for a
reason - the land of the Turkic peoples who inhabited Central Asia
and united under together. Currently, nations and nationalities of the
Turkestan region formed their own sovereign states, and every year
they prove their country names in the world community. Political,
economic importance of Turkestan, which became the gold wire
between Asia and Europe was always very high. So systematically
various aggressive actions were made by several great powers. As a
result of expansionary policy of colonization of the Russian Empire -
the Turkestan has appeared.
Abstract: Studies in neuroscience suggest that both global and
local feature information are crucial for perception and recognition of
faces. It is widely believed that local feature is less sensitive to
variations caused by illumination, expression and illumination. In
this paper, we target at designing and learning local features for face
recognition. We designed three types of local features. They are
semi-global feature, local patch feature and tangent shape feature.
The designing of semi-global feature aims at taking advantage of
global-like feature and meanwhile avoiding suppressing AdaBoost
algorithm in boosting weak classifies established from small local
patches. The designing of local patch feature targets at automatically
selecting discriminative features, and is thus different with traditional
ways, in which local patches are usually selected manually to cover
the salient facial components. Also, shape feature is considered in
this paper for frontal view face recognition. These features are
selected and combined under the framework of boosting algorithm
and cascade structure. The experimental results demonstrate that the
proposed approach outperforms the standard eigenface method and
Bayesian method. Moreover, the selected local features and
observations in the experiments are enlightening to researches in
local feature design in face recognition.
Abstract: This paper presents a novel two-phase hybrid optimization algorithm with hybrid genetic operators to solve the optimal control problem of a single stage hybrid manufacturing system. The proposed hybrid real coded genetic algorithm (HRCGA) is developed in such a way that a simple real coded GA acts as a base level search, which makes a quick decision to direct the search towards the optimal region, and a local search method is next employed to do fine tuning. The hybrid genetic operators involved in the proposed algorithm improve both the quality of the solution and convergence speed. The phase–1 uses conventional real coded genetic algorithm (RCGA), while optimisation by direct search and systematic reduction of the size of search region is employed in the phase – 2. A typical numerical example of an optimal control problem with the number of jobs varying from 10 to 50 is included to illustrate the efficacy of the proposed algorithm. Several statistical analyses are done to compare the validity of the proposed algorithm with the conventional RCGA and PSO techniques. Hypothesis t – test and analysis of variance (ANOVA) test are also carried out to validate the effectiveness of the proposed algorithm. The results clearly demonstrate that the proposed algorithm not only improves the quality but also is more efficient in converging to the optimal value faster. They can outperform the conventional real coded GA (RCGA) and the efficient particle swarm optimisation (PSO) algorithm in quality of the optimal solution and also in terms of convergence to the actual optimum value.
Abstract: C-control chart assumes that process nonconformities follow a Poisson distribution. In actuality, however, this Poisson distribution does not always occur. A process control for semiconductor based on a Poisson distribution always underestimates the true average amount of nonconformities and the process variance. Quality is described more accurately if a compound Poisson process is used for process control at this time. A cumulative sum (CUSUM) control chart is much better than a C control chart when a small shift will be detected. This study calculates one-sided CUSUM ARLs using a Markov chain approach to construct a CUSUM control chart with an underlying Poisson-Gamma compound distribution for the failure mechanism. Moreover, an actual data set from a wafer plant is used to demonstrate the operation of the proposed model. The results show that a CUSUM control chart realizes significantly better performance than EWMA.
Abstract: Centrally controlled authentication and authorization services can provide enterprise with an increase in security, more flexible access control solutions and an increased users' trust. By using redirections, users of all Web-based applications within an organization are authenticated at a single well known and secure Web site and using secure communication protocol. Users are first authenticated at the central server using their domain wide credentials before being redirected to a particular Web-based application. The central authentication server will then provide others with pertinence authorization related particulars and credentials of the authenticated user to the specific application. The trust between the clients and the server hosts is established by secure session keys exchange. Case- studies are provided to demonstrate the usefulness and flexibility of the proposed solution.