Abstract: In designing of condensers, the prediction of pressure
drop is as important as the prediction of heat transfer coefficient.
Modeling of two phase flow, particularly liquid – vapor flow under
diabatic conditions inside a horizontal tube using CFD analysis is
difficult with the available two phase models in FLUENT due to
continuously changing flow patterns. In the present analysis, CFD
analysis of two phase flow of refrigerants inside a horizontal tube of
inner diameter, 0.0085 m and 1.2 m length is carried out using
homogeneous model under adiabatic conditions. The refrigerants
considered are R22, R134a and R407C. The analysis is performed at
different saturation temperatures and at different flow rates to
evaluate the local frictional pressure drop. Using Homogeneous
model, average properties are obtained for each of the refrigerants
that is considered as single phase pseudo fluid. The so obtained
pressure drop data is compared with the separated flow models
available in literature.
Abstract: Available Bit Rate Service (ABR) is the lower priority
service and the better service for the transmission of data. On wireline
ATM networks ABR source is always getting the feedback from
switches about increase or decrease of bandwidth according to the
changing network conditions and minimum bandwidth is guaranteed.
In wireless networks guaranteeing the minimum bandwidth is really a
challenging task as the source is always in mobile and traveling from
one cell to another cell. Re establishment of virtual circuits from start
to end every time causes the delay in transmission. In our proposed
solution we proposed the mechanism to provide more available
bandwidth to the ABR source by re-usage of part of old Virtual
Channels and establishing the new ones. We want the ABR source to
transmit the data continuously (non-stop) inorderto avoid the delay.
In worst case scenario at least minimum bandwidth is to be allocated.
In order to keep the data flow continuously, priority is given to the
handoff ABR call against new ABR call.
Abstract: Software effort estimation is the process of predicting
the most realistic use of effort required to develop or maintain
software based on incomplete, uncertain and/or noisy input. Effort
estimates may be used as input to project plans, iteration plans,
budgets. There are various models like Halstead, Walston-Felix,
Bailey-Basili, Doty and GA Based models which have already used
to estimate the software effort for projects. In this study Statistical
Models, Fuzzy-GA and Neuro-Fuzzy (NF) Inference Systems are
experimented to estimate the software effort for projects. The
performances of the developed models were tested on NASA
software project datasets and results are compared with the Halstead,
Walston-Felix, Bailey-Basili, Doty and Genetic Algorithm Based
models mentioned in the literature. The result shows that the NF
Model has the lowest MMRE and RMSE values. The NF Model
shows the best results as compared with the Fuzzy-GA based hybrid
Inference System and other existing Models that are being used for
the Effort Prediction with lowest MMRE and RMSE values.
Abstract: The objective of this study was to improve our
understanding of vulnerability and environmental change; it's causes
basically show the intensity, its distribution and human-environment
effect on the ecosystem in the Apodi Valley Region, This paper is
identify, assess and classify vulnerability and environmental change
in the Apodi valley region using a combined approach of landscape
pattern and ecosystem sensitivity. Models were developed using the
following five thematic layers: Geology, geomorphology, soil,
vegetation and land use/cover, by means of a Geographical
Information Systems (GIS)-based on hydro-geophysical parameters.
In spite of the data problems and shortcomings, using ESRI-s ArcGIS
9.3 program, the vulnerability score, to classify, weight and combine
a number of 15 separate land cover classes to create a single indicator
provides a reliable measure of differences (6 classes) among regions
and communities that are exposed to similar ranges of hazards.
Indeed, the ongoing and active development of vulnerability
concepts and methods have already produced some tools to help
overcome common issues, such as acting in a context of high
uncertainties, taking into account the dynamics and spatial scale of
asocial-ecological system, or gathering viewpoints from different
sciences to combine human and impact-based approaches. Based on
this assessment, this paper proposes concrete perspectives and
possibilities to benefit from existing commonalities in the
construction and application of assessment tools.
Abstract: In this work, ionic liquids (ILs) for CO2 capturing in typical absorption/stripper process are considered. The use of ionic liquids is considered to be cost-effective because it requires less energy for solvent recovery compared to other conventional processes. A mathematical model is developed for the process based on Peng-Robinson (PR) equation of state (EoS) which is validated with experimental data for various solutions involving CO2. The model is utilized to study the sorbent and energy demand for three types of ILs at specific CO2 capturing rates. The energy demand is manifested by the vapor-liquid equilibrium temperature necessary to remove the captured CO2 from the used solvent in the regeneration step. It is found that higher recovery temperature is required for solvents with higher solubility coefficient. For all ILs, the temperature requirement is less than that required by the typical monoethanolamine (MEA) solvent. The effect of the CO2 loading in the sorbent stream on the process performance is also examined.
Abstract: The investigating and assessing the effects of
relaxation training on the levels of state anxiety concerning first year
female nursing students at their initial experience in clinical setting.
This research is a quasi experimental study that was carried out in
nursing and midwifery faculty of Tehran university of medical
sciences .The sample of research consists 60 first term female
nursing students were selected through convenience and random
sampling. 30 of them were the experimental group and 30 of them
were in control group. The Instruments of data-collection has been a
questionnaire which consists of 3 parts. The first part includes 10
questions about demographic characteristics .the second part includes
20 question about anxiety (test 'Spielberg' ). The 3rd part includes
physiological indicators of anxiety (BP, P, R, body temperature). The
statistical tests included t-test and and fisher test, Data were
analyzed by SPSS software.
Abstract: carbonylation of methanol in homogenous phase is
one of the major routesfor production of acetic acid. Amongst group
VIII metal catalysts used in this process iridium has displayed the
best capabilities. To investigate effect of operating parameters like:
temperature, pressure, methyl iodide, methyl acetate, iridium,
ruthenium, and water concentrations on the reaction rate,
experimental design for this system based upon central composite
design (CCD) was utilized. Statistical rate equation developed by this
method contained individual, interactions and curvature effects of
parameters on the reaction rate. The model with p-value less than
0.0001 and R2 values greater than 0.9; confirmeda satisfactory fitness
of the experimental and theoretical studies. In other words, the
developed model and experimental data obtained passed all
diagnostic tests establishing this model as a statistically significant.
Abstract: Multimedia information availability has increased
dramatically with the advent of video broadcasting on handheld
devices. But with this availability comes problems of maintaining the
security of information that is displayed in public. ISMA Encryption
and Authentication (ISMACryp) is one of the chosen technologies for
service protection in DVB-H (Digital Video Broadcasting-
Handheld), the TV system for portable handheld devices. The
ISMACryp is encoded with H.264/AVC (advanced video coding),
while leaving all structural data as it is. Two modes of ISMACryp are
available; the CTR mode (Counter type) and CBC mode (Cipher
Block Chaining) mode. Both modes of ISMACryp are based on 128-
bit AES algorithm. AES algorithms are more complex and require
larger time for execution which is not suitable for real time
application like live TV. The proposed system aims to gain a deep
understanding of video data security on multimedia technologies and
to provide security for real time video applications using selective
encryption for H.264/AVC. Five level of security proposed in this
paper based on the content of NAL unit in Baseline Constrain profile
of H.264/AVC. The selective encryption in different levels provides
encryption of intra-prediction mode, residue data, inter-prediction
mode or motion vectors only. Experimental results shown in this
paper described that fifth level which is ISMACryp provide higher
level of security with more encryption time and the one level provide
lower level of security by encrypting only motion vectors with lower
execution time without compromise on compression and quality of
visual content. This encryption scheme with compression process
with low cost, and keeps the file format unchanged with some direct
operations supported. Simulation was being carried out in Matlab.
Abstract: There are many situations where input feature vectors are incomplete and methods to tackle the problem have been studied for a long time. A commonly used procedure is to replace each missing value with an imputation. This paper presents a method to perform categorical missing data imputation from numerical and categorical variables. The imputations are based on Simpson-s fuzzy min-max neural networks where the input variables for learning and classification are just numerical. The proposed method extends the input to categorical variables by introducing new fuzzy sets, a new operation and a new architecture. The procedure is tested and compared with others using opinion poll data.
Abstract: The healthcare environment is generally perceived as
being information rich yet knowledge poor. However, there is a lack
of effective analysis tools to discover hidden relationships and trends
in data. In fact, valuable knowledge can be discovered from
application of data mining techniques in healthcare system. In this
study, a proficient methodology for the extraction of significant
patterns from the Coronary Heart Disease warehouses for heart
attack prediction, which unfortunately continues to be a leading cause
of mortality in the whole world, has been presented. For this purpose,
we propose to enumerate dynamically the optimal subsets of the
reduced features of high interest by using rough sets technique
associated to dynamic programming. Therefore, we propose to
validate the classification using Random Forest (RF) decision tree to
identify the risky heart disease cases. This work is based on a large
amount of data collected from several clinical institutions based on
the medical profile of patient. Moreover, the experts- knowledge in
this field has been taken into consideration in order to define the
disease, its risk factors, and to establish significant knowledge
relationships among the medical factors. A computer-aided system is
developed for this purpose based on a population of 525 adults. The
performance of the proposed model is analyzed and evaluated based
on set of benchmark techniques applied in this classification problem.
Abstract: In this paper, a benchmarking framework is presented
for the performance assessment of irrigations systems. Firstly, a data
envelopment analysis (DEA) is applied to measure the technical
efficiency of irrigation systems. This method, based on linear
programming, aims to determine a consistent efficiency ranking of
irrigation systems in which known inputs, such as water volume
supplied and total irrigated area, and a given output corresponding to
the total value of irrigation production are taken into account
simultaneously. Secondly, in order to examine the irrigation
efficiency in more detail, a cross – system comparison is elaborated
using a performance indicators set selected by IWMI. The above
methodologies were applied in Thessaloniki plain, located in
Northern Greece while the results of the application are presented and
discussed. The conjunctive use of DEA and performance indicators
seems to be a very useful tool for efficiency assessment and
identification of best practices in irrigation systems management.
Abstract: The paper deals with quality labels used in the food products market, especially with labels of quality, labels of origin, and labels of organic farming. The aim of the paper is to identify perception of these labels by consumers in the Czech Republic. The first part refers to the definition and specification of food quality labels that are relevant in the Czech Republic. The second part includes the discussion of marketing research results. Data were collected with personal questioning method. Empirical findings on 150 respondents are related to consumer awareness and perception of national and European food quality labels used in the Czech Republic, attitudes to purchases of labelled products, and interest in information regarding the labels. Statistical methods, in the concrete Pearson´s chi-square test of independence, coefficient of contingency, and coefficient of association are used to determinate if significant differences do exist among selected demographic categories of Czech consumers.
Abstract: Experimental data from an atmospheric air/water terrain slugging case has been made available by the Shell Amsterdam research center, and has been subject to numerical simulation and comparison with a one-dimensional two-phase slug tracking simulator under development at the Norwegian University of Science and Technology. The code is based on tracking of liquid slugs in pipelines by use of a Lagrangian grid formulation implemented in Cµ by use of object oriented techniques. An existing hybrid spatial discretization scheme is tested, in which the stratified regions are modelled by the two-fluid model. The slug regions are treated incompressible, thus requiring a single momentum balance over the whole slug. Upon comparison with the experimental data, the period of the simulated severe slugging cycle is observed to be sensitive to slug generation in the horizontal parts of the system. Two different slug initiation methods have been tested with the slug tracking code, and grid dependency has been investigated.
Abstract: The paper presents an approach for handling uncertain
information in deductive databases using multivalued logics. Uncertainty
means that database facts may be assigned logical values other
than the conventional ones - true and false. The logical values represent
various degrees of truth, which may be combined and propagated
by applying the database rules. A corresponding multivalued database
semantics is defined. We show that it extends successful conventional
semantics as the well-founded semantics, and has a polynomial time
data complexity.
Abstract: Decision fusion is one of hot research topics in
classification area, which aims to achieve the best possible
performance for the task at hand. In this paper, we
investigate the usefulness of this concept to improve change
detection accuracy in remote sensing. Thereby, outputs of
two fuzzy change detectors based respectively on
simultaneous and comparative analysis of multitemporal
data are fused by using fuzzy integral operators. This
method fuses the objective evidences produced by the
change detectors with respect to fuzzy measures that express
the difference of performance between them. The proposed
fusion framework is evaluated in comparison with some
ordinary fuzzy aggregation operators. Experiments carried
out on two SPOT images showed that the fuzzy integral was
the best performing. It improves the change detection
accuracy while attempting to equalize the accuracy rate in
both change and no change classes.
Abstract: RFID (Radio Frequency IDentification) system has
been widely used in our life, such as transport systems, passports,
automotive, animal tracking, human implants, library, and so on.
However, the RFID authentication protocols between RF (Radio
Frequency) tags and the RF readers have been bring about various
privacy problems that anonymity of the tags, tracking, eavesdropping,
and so on. Many researchers have proposed the solution of the
problems. However, they still have the problem, such as location
privacy, mutual authentication. In this paper, we show the problems of
the previous protocols, and then we propose a more secure and
efficient RFID authentication protocol.
Abstract: Road crashes not only claim lives and inflict injuries but also create economic burden to the society due to loss of productivity. The problem of deaths and injuries as a result of road traffic crashes is now acknowledged to be a global phenomenon with authorities in virtually all countries of the world concerned about the growth in the number of people killed and seriously injured on their roads. However, the road crash scenario of a developing country like Bangladesh is much worse comparing with this of developed countries. For developing proper countermeasures it is necessary to identify the factors affecting crash occurrences. The objectives of the study is to examine the effect of district wise road infrastructure, socioeconomic and demographic features on crash occurrence .The unit of analysis will be taken as individual district which has not been explored much in the past. Reported crash data obtained from Bangladesh Road Transport Authority (BRTA) from the year 2004 to 2010 are utilized to develop negative binomial model. The model result will reveal the effect of road length (both paved and unpaved), road infrastructure and several socio economic characteristics on district level crash frequency in Bangladesh.
Abstract: This study examines the impact of working capital
management on firms- performance and market value of the firms in
Nigeria. A sample of fifty four non-financial quoted firms in Nigeria
listed on the Nigeria Stock Exchange was used for this study. Data
were collected from annual reports of the sampled firms for the
period 1995-2009. This result shows there is a significant negative
relationship between cash conversion cycle and market valuation
and firm-s performance. It also shows that debt ratio is positively
related to market valuation and negatively related firm-s
performance. The findings confirm that there is a significant
relationship between Market valuation, profitability and working
capital component in line with previous studies. This mean that
Nigeria firms should ensure adequate management of working
capital especially cash conversion cycle components of account
receivables, account payables and inventories, as efficiency working
capital management is expected to contribute positively to the firms-
market value.
Abstract: This research aims to develop and evaluate a training
course to promote learning activities of 2nd year, Suan Sunandha
Rajabhat University, faculty of education students using multiple
intelligences theory. The process is divided into two phases: Phase 1
development of training course to promote learning activities
consisting of principles, objectives of the course, structure, training
duration, content, training materials, training activities, media
training, monitoring, measurement and evaluation quality of the
course. Phase 2 evaluation efficiency of training course was to use
the improved curriculum with experimental group which is 2nd year,
Suan Sunandha Rajabhat University, faculty of education students
was drawn randomly 152 students. The experimental pattern was
randomized Control Group Pre-Test Post-Test Design, Analysis Data
by t-Test with the software SPFSS for Windows. Research has shown
that: 1). the ability of teaching and learning according to the theory of
multiple intelligences after training is higher than before training
significantly in statistic at .01 level, 2). The satisfaction of students
to the training courses was overall at the highest level.
Abstract: In this paper, the implementation of a rule-based
intuitive reasoner is presented. The implementation included two
parts: the rule induction module and the intuitive reasoner. A large
weather database was acquired as the data source. Twelve weather
variables from those data were chosen as the “target variables"
whose values were predicted by the intuitive reasoner. A “complex"
situation was simulated by making only subsets of the data available
to the rule induction module. As a result, the rules induced were
based on incomplete information with variable levels of certainty.
The certainty level was modeled by a metric called "Strength of
Belief", which was assigned to each rule or datum as ancillary
information about the confidence in its accuracy. Two techniques
were employed to induce rules from the data subsets: decision tree
and multi-polynomial regression, respectively for the discrete and the
continuous type of target variables. The intuitive reasoner was tested
for its ability to use the induced rules to predict the classes of the
discrete target variables and the values of the continuous target
variables. The intuitive reasoner implemented two types of
reasoning: fast and broad where, by analogy to human thought, the
former corresponds to fast decision making and the latter to deeper
contemplation. . For reference, a weather data analysis approach
which had been applied on similar tasks was adopted to analyze the
complete database and create predictive models for the same 12
target variables. The values predicted by the intuitive reasoner and
the reference approach were compared with actual data. The intuitive
reasoner reached near-100% accuracy for two continuous target
variables. For the discrete target variables, the intuitive reasoner
predicted at least 70% as accurately as the reference reasoner. Since
the intuitive reasoner operated on rules derived from only about 10%
of the total data, it demonstrated the potential advantages in dealing
with sparse data sets as compared with conventional methods.