Abstract: The process for predicting the ballistic properties of a liquid rocket engine is based on the quantitative estimation of idealized performance deviations. In this aim, an equilibrium chemistry procedure is firstly developed and implemented in a Fortran routine. The thermodynamic formulation allows for the calculation of the theoretical performances of a rocket thrust chamber. In a second step, a computational fluid dynamic analysis of the turbulent reactive flow within the chamber is performed using a finite volume approach. The obtained values for the “quasi-real" performances account for both turbulent mixing and chemistryturbulence coupling. In the present work, emphasis is made on the combustion efficiency performance for which deviation is mainly due to radial gradients of static temperature and mixture ratio. Numerical values of the characteristic velocity are successfully compared with results from an industry-used code. The results are also confronted with the experimental data of a laboratory-scale rocket engine.
Abstract: Influence of octane and benzene on plant cell
ultrastructure and enzymes of basic metabolism, such as nitrogen
assimilation and energy generation have been studied. Different
plants: perennial ryegrass (Lolium perenne) and alfalfa (Medicago
sativa); crops- maize (Zea mays L.) and bean (Phaseolus vulgaris);
shrubs – privet (Ligustrum sempervirens) and trifoliate orange
(Poncirus trifoliate); trees - poplar (Populus deltoides) and white
mulberry (Morus alba L.) were exposed to hydrocarbons of different
concentrations (1, 10 and 100 mM). Destructive changes in bean and
maize leaves cells ultrastructure under the influence of benzene
vapour were revealed at the level of photosynthetic and energy
generation subcellular organells. Different deviations at the level of
subcellular organelles structure and distribution were observed in
alfalfa and ryegrass root cells under the influence of benzene and
octane, absorbed through roots. The level of destructive changes is
concentration dependent. Benzene at low 1 and 10 mM concentration
caused the increase in glutamate dehydrogenase (GDH) activity in
maize roots and leaves and in poplar and mulberry shoots, though to
higher extent in case of lower, 1mM concentration. The induction
was more intensive in plant roots. The highest tested 100mM
concentration of benzene was inhibitory to the enzyme in all plants.
Octane caused induction of GDH in all grassy plants at all tested
concentrations; however the rate of induction decreased parallel to
increase of the hydrocarbon concentration. Octane at concentration 1
mM caused induction of GDH in privet, trifoliate and white mulberry
shoots. The highest, 100mM octane was characterized by inhibitory
effect to GDH activity in all plants. Octane had inductive effect on
malate dehydrogenase in almost all plants and tested concentrations,
indicating the intensification of Trycarboxylic Acid Cycle.
The data could be suggested for elaboration of criteria for plant
selection for phytoremediation of oil hydrocarbons contaminated
soils.
Abstract: Classification is one of the primary themes in
computational biology. The accuracy of classification strongly
depends on quality of a dataset, and we need some method to
evaluate this quality. In this paper, we propose a new graphical
analysis method using 'Membership-Deviation Graph (MDG)' for
analyzing quality of a dataset. MDG represents degree of
membership and deviations for instances of a class in the dataset. The
result of MDG analysis is used for understanding specific feature and
for selecting best feature for classification.
Abstract: In this study we present our developed formative
assessment tool for students' assignments. The tool enables lecturers
to define assignments for the course and assign each problem in each
assignment a list of criteria and weights by which the students' work
is evaluated. During assessment, the lecturers feed the scores for each
criterion with justifications. When the scores of the current
assignment are completely fed in, the tool automatically generates
reports for both students and lecturers. The students receive a report
by email including detailed description of their assessed work, their
relative score and their progress across the criteria along the course
timeline. This information is presented via charts generated
automatically by the tool based on the scores fed in. The lecturers
receive a report that includes summative (e.g., averages, standard
deviations) and detailed (e.g., histogram) data of the current
assignment. This information enables the lecturers to follow the class
achievements and adjust the learning process accordingly. The tool
was examined on two pilot groups of college students that study a
course in (1) Object-Oriented Programming (2) Plane Geometry.
Results reveal that most of the students were satisfied with the
assessment process and the reports produced by the tool. The
lecturers who used the tool were also satisfied with the reports and
their contribution to the learning process.
Abstract: Concerns about low levels of children-s physical activity and motor skill development, prompted the Ministry of Education to trial a physical activity pilot project (PAPP) in 16 New Zealand primary schools. The project comprised professional development and training in physical education for lead teachers and introduced four physical activity coordinators to liaise with and increase physical activity opportunities in the pilot schools. A survey of generalist teachers (128 baseline, 155 post-intervention) from these schools looked at timetabled physical activity sessions and issues related to teaching physical education. The authors calculated means and standard deviations of data relating to timetabled PE sessions and used a one-way analysis of variance to determine significant differences. Results indicated time devoted to physical activity related subjects significantly increased over the course of the intervention. Teacher-s reported improved confidence and competence, which resulted in an improvement in quality physical education delivered more often.
Abstract: In this paper, the requirement for Coke quality
prediction, its role in Blast furnaces, and the model output is
explained. By applying method of Artificial Neural Networking
(ANN) using back propagation (BP) algorithm, prediction model has
been developed to predict CSR. Important blast furnace functions
such as permeability, heat exchanging, melting, and reducing
capacity are mostly connected to coke quality. Coke quality is further
dependent upon coal characterization and coke making process
parameters. The ANN model developed is a useful tool for process
experts to adjust the control parameters in case of coke quality
deviations. The model also makes it possible to predict CSR for new
coal blends which are yet to be used in Coke Plant. Input data to the
model was structured into 3 modules, for tenure of past 2 years and
the incremental models thus developed assists in identifying the
group causing the deviation of CSR.
Abstract: Multi-residue analysis method for penicillins was
developed and validated in bovine muscle, chicken, milk, and flatfish.
Detection was based on liquid chromatography tandem mass
spectrometry (LC/MS/MS). The developed method was validated for
specificity, precision, recovery, and linearity. The analytes were
extracted with 80% acetonitrile and clean-up by a single
reversed-phase solid-phase extraction step. Six penicillins presented
recoveries higher than 76% with the exception of Amoxicillin
(59.7%). Relative standard deviations (RSDs) were not more than
10%. LOQs values ranged from 0.1 and to 4.5 ug/kg. The method was
applied to 128 real samples. Benzylpenicillin was detected in 15
samples and Cloxacillin was detected in 7 samples. Oxacillin was
detected in 2 samples. But the detected levels were under the MRL
levels for penicillins in samples.
Abstract: The thermal, epithermal and fast fluxes were
calculated for three irradiation channels at Egypt Second Research
Reactor (ETRR-2) using CITVAP code. The validity of the
calculations was verified by experimental measurements. There are
some deviations between measurements and calculations. This is due
to approximations in the calculation models used, homogenization of
regions, condensation of energy groups and uncertainty in nuclear
data used. Neutron flux data for the three irradiation channels are
now available. This would enable predicting the irradiation
conditions needed for future radioisotope production.
Abstract: This paper describes a methodology for remote
performance monitoring of retail refrigeration systems. The proposed
framework starts with monitoring of the whole refrigeration circuit
which allows detecting deviations from expected behavior caused by
various faults and degradations. The subsequent diagnostics methods
drill down deeper in the equipment hierarchy to more specifically
determine root causes. An important feature of the proposed concept
is that it does not require any additional sensors, and thus, the
performance monitoring solution can be deployed at a low
installation cost. Moreover only a minimum of contextual
information is required, which also substantially reduces time and
cost of the deployment process.
Abstract: Emerging Bio-engineering fields such as Brain
Computer Interfaces, neuroprothesis devices and modeling and
simulation of neural networks have led to increased research activity
in algorithms for the detection, isolation and classification of Action
Potentials (AP) from noisy data trains. Current techniques in the field
of 'unsupervised no-prior knowledge' biosignal processing include
energy operators, wavelet detection and adaptive thresholding. These
tend to bias towards larger AP waveforms, AP may be missed due to
deviations in spike shape and frequency and correlated noise
spectrums can cause false detection. Also, such algorithms tend to
suffer from large computational expense.
A new signal detection technique based upon the ideas of phasespace
diagrams and trajectories is proposed based upon the use of a
delayed copy of the AP to highlight discontinuities relative to
background noise. This idea has been used to create algorithms that
are computationally inexpensive and address the above problems.
Distinct AP have been picked out and manually classified from
real physiological data recorded from a cockroach. To facilitate
testing of the new technique, an Auto Regressive Moving Average
(ARMA) noise model has been constructed bases upon background
noise of the recordings. Along with the AP classification means this
model enables generation of realistic neuronal data sets at arbitrary
signal to noise ratio (SNR).
Abstract: The purpose of the study reported here was designing Information Dissemination System (IDS) based E-learning in agricultural of Iran. A questionnaire was developed to designing Information Dissemination System. The questionnaire was distributed to 96 extension agents who work for Management of Extension and Farming System of Khuzestan province of Iran. Data collected were analyzed using the Statistical Package for the Social Sciences (SPSS). Appropriate statistical procedures for description (frequencies, percent, means, and standard deviations) were used. In this study there was a significant relationship between the age , IT skill and knowledge, years of extension work, the extend of information seeking motivation, level of job satisfaction and level of education with use of information technology by extension agent. According to extension agents five factors were ranked respectively as five top essential items to designing Information Dissemination System (IDS) based E-learning in agricultural of Iran. These factors include: 1) Establish communication between farmers, coordinators (extension agents), agricultural experts, research centers, and community by information technology. 2) The communication between all should be mutual. 3) The information must be based farmers need. 4) Internet used as a facility to transfer the advanced agricultural information to the farming community. 5) Farmers can be illiterate and speak a local and they are not expected to use the system directly. Knowledge produced by the agricultural scientist must be transformed in to computer understandable presentation. To designing Information Dissemination System, electronic communication, in the agricultural society and rural areas must be developed. This communication must be mutual between all factors.
Abstract: A study was conducted to formally characterize
notebook computer performance under various environmental and
usage conditions. Software was developed to collect data from the
operating system of the computer. An experiment was conducted to
evaluate the performance parameters- variations, trends, and
correlations, as well as the extreme value they can attain in various
usage and environmental conditions. An automated software script
was written to simulate user activity. The variability of each
performance parameter was addressed by establishing the empirical
relationship between performance parameters. These equations were
presented as baseline estimates for performance parameters, which
can be used to detect system deviations from normal operation and
for prognostic assessment. The effect of environmental factors,
including different power sources, ambient temperatures, humidity,
and usage, on performance parameters of notebooks was studied.
Abstract: Psoriasis is a widespread skin disease affecting up to 2% population with plaque psoriasis accounting to about 80%. It can be identified as a red lesion and for the higher severity the lesion is usually covered with rough scale. Psoriasis Area Severity Index (PASI) scoring is the gold standard method for measuring psoriasis severity. Scaliness is one of PASI parameter that needs to be quantified in PASI scoring. Surface roughness of lesion can be used as a scaliness feature, since existing scale on lesion surface makes the lesion rougher. The dermatologist usually assesses the severity through their tactile sense, therefore direct contact between doctor and patient is required. The problem is the doctor may not assess the lesion objectively. In this paper, a digital image analysis technique is developed to objectively determine the scaliness of the psoriasis lesion and provide the PASI scaliness score. Psoriasis lesion is modelled by a rough surface. The rough surface is created by superimposing a smooth average (curve) surface with a triangular waveform. For roughness determination, a polynomial surface fitting is used to estimate average surface followed by a subtraction between rough and average surface to give elevation surface (surface deviations). Roughness index is calculated by using average roughness equation to the height map matrix. The roughness algorithm has been tested to 444 lesion models. From roughness validation result, only 6 models can not be accepted (percentage error is greater than 10%). These errors occur due the scanned image quality. Roughness algorithm is validated for roughness measurement on abrasive papers at flat surface. The Pearson-s correlation coefficient of grade value (G) of abrasive paper and Ra is -0.9488, its shows there is a strong relation between G and Ra. The algorithm needs to be improved by surface filtering, especially to overcome a problem with noisy data.
Abstract: Recurrent event data is a special type of multivariate
survival data. Dynamic and frailty models are one of the approaches
that dealt with this kind of data. A comparison between these two
models is studied using the empirical standard deviation of the
standardized martingale residual processes as a way of assessing the
fit of the two models based on the Aalen additive regression model.
Here we found both approaches took heterogeneity into account and
produce residual standard deviations close to each other both in the
simulation study and in the real data set.
Abstract: In Multiple Sclerosis, pathological changes in the
brain results in deviations in signal intensity on Magnetic Resonance
Images (MRI). Quantitative analysis of these changes and their
correlation with clinical finding provides important information for
diagnosis. This constitutes the objective of our work. A new approach
is developed. After the enhancement of images contrast and the brain
extraction by mathematical morphology algorithm, we proceed to the
brain segmentation. Our approach is based on building statistical
model from data itself, for normal brain MRI and including clustering
tissue type. Then we detect signal abnormalities (MS lesions) as a
rejection class containing voxels that are not explained by the built
model. We validate the method on MR images of Multiple Sclerosis
patients by comparing its results with those of human expert
segmentation.
Abstract: This paper is concerned with the application of small
rating Capacitive Energy Storage units for the improvement of
Automatic Generation Control of a multiunit multiarea power
system. Generation Rate Constraints are also considered in the
investigations. Integral Squared Error technique is used to obtain the
optimal integral gain settings by minimizing a quadratic performance
index. Simulation studies reveal that with CES units, the deviations
in area frequencies and inter-area tie-power are considerably
improved in terms of peak deviations and settling time as compared
to that obtained without CES units.
Abstract: Actual load, material characteristics and other
quantities often differ from the design values. This can cause worse
function, shorter life or failure of a civil engineering structure, a
machine, vehicle or another appliance. The paper shows main causes
of the uncertainties and deviations and presents a systematic
approach and efficient tools for their elimination or mitigation of
consequences. Emphasis is put on the design stage, which is most
important for reliability ensuring. Principles of robust design and
important tools are explained, including FMEA, sensitivity analysis
and probabilistic simulation methods. The lifetime prediction of
long-life objects can be improved by long-term monitoring of the
load response and damage accumulation in operation. The condition
evaluation of engineering structures, such as bridges, is often based
on visual inspection and verbal description. Here, methods based on
fuzzy logic can reduce the subjective influences.