Abstract: The springs located in urban areas are the outpouring
of surface water, which can serve as water supply, effluent receptors
and important local macro-drainage elements. With unplanned
occupation, non-compliance with environmental legislation and the
importance of these water bodies, it is vital to analyze the springs
within urban areas, considering the Brazilian forest code. This paper
submits an analysis and discussion methodology proposal of
environmental compliance functions of urban springs, by means of
G.I.S. - Geographic Information System analysis - and in situ
analysis. The case study included two springs which exhibit a history
of occupation along its length, with different degrees of impact. The
proposed method is effective and easy to apply, representing a
powerful tool for analyzing the environmental conditions of springs
in urban areas.
Abstract: In this paper back-propagation artificial neural
network (BPANN) is employed to predict the limiting drawing ratio
(LDR) of the deep drawing process. To prepare a training set for
BPANN, some finite element simulations were carried out. die and
punch radius, die arc radius, friction coefficient, thickness, yield
strength of sheet and strain hardening exponent were used as the
input data and the LDR as the specified output used in the training of
neural network. As a result of the specified parameters, the program
will be able to estimate the LDR for any new given condition.
Comparing FEM and BPANN results, an acceptable correlation was
found.
Abstract: This paper describes about dynamic reconfiguration to
miniaturize arithmetic circuits in general-purpose processor. Dynamic
reconfiguration is a technique to realize required functions by
changing hardware construction during operation. The proposed
arithmetic circuit performs floating-point arithmetic which is
frequently used in science and technology. The data format is
floating-point based on IEEE754. The proposed circuit is designed
using VHDL, and verified the correct operation by simulations and
experiments.
Abstract: In this paper, a simple microfluidic device for monitoring algal cell behavior is proposed. An array of algal microwells is fabricated by PDMS soft-lithography using X-ray LIGA mold, placed on a glass substrate. Two layers of replicated PDMS and substrate are attached by oxygen plasma bonding, creating a microchannel for the microfluidic system. Algal cell are loaded into the microfluidic device, which provides positive charge on the bottom surface of wells. Algal cells, which are negative charged, can be attracted to the bottom of the wells via electrostatic interaction. By varying the concentration of algal cells in the loading suspension, it is possible to obtain wells with a single cell. Liquid medium for cells monitoring are flown continuously over the wells, providing nutrient and waste exchange between the well and the main flow. This device could lead to the uncovering of the quantitative biology of the algae, which is a key to effective and extensive algal utilizations in the field of biotechnology, food industry and bioenergy research and developments.
Abstract: Cross layer optimization based on utility functions has
been recently studied extensively, meanwhile, numerous types of
utility functions have been examined in the corresponding literature.
However, a major drawback is that most utility functions take a fixed
mathematical form or are based on simple combining, which can
not fully exploit available information. In this paper, we formulate a
framework of cross layer optimization based on Adaptively Weighted
Utility Functions (AWUF) for fairness balancing in OFDMA networks.
Under this framework, a two-step allocation algorithm is
provided as a sub-optimal solution, whose control parameters can be
updated in real-time to accommodate instantaneous QoS constrains.
The simulation results show that the proposed algorithm achieves
high throughput while balancing the fairness among multiple users.
Abstract: State-of-the-art methods for secondary structure (Porter, Psi-PRED, SAM-T99sec, Sable) and solvent accessibility (Sable, ACCpro) predictions use evolutionary profiles represented by the position specific scoring matrix (PSSM). It has been demonstrated that evolutionary profiles are the most important features in the feature space for these predictions. Unfortunately applying PSSM matrix leads to high dimensional feature spaces that may create problems with parameter optimization and generalization. Several recently published suggested that applying feature extraction for the PSSM matrix may result in improvements in secondary structure predictions. However, none of the top performing methods considered here utilizes dimensionality reduction to improve generalization. In the present study, we used simple and fast methods for features selection (t-statistics, information gain) that allow us to decrease the dimensionality of PSSM matrix by 75% and improve generalization in the case of secondary structure prediction compared to the Sable server.
Abstract: In this manuscript, we discuss the problem of determining the optimum stratification of a study (or main) variable based on the auxiliary variable that follows a uniform distribution. If the stratification of survey variable is made using the auxiliary variable it may lead to substantial gains in precision of the estimates. This problem is formulated as a Nonlinear Programming Problem (NLPP), which turn out to multistage decision problem and is solved using dynamic programming technique.
Abstract: This paper discusses the approach of real-time
controlling of the energy management system using the data
acquisition tool of LabVIEW. The main idea of this inspiration was
to interface the Station (PC) with the system and publish the data on
internet using LabVIEW. In this venture, controlling and switching of
3 phase AC loads are effectively and efficiently done. The phases are
also sensed through devices. In case of any failure the attached
generator starts functioning automatically. The computer sends
command to the system and system respond to the request. The
modern feature is to access and control the system world-wide using
world wide web (internet). This controlling can be done at any time
from anywhere to effectively use the energy especially in developing
countries where energy management is a big problem. In this system
totally integrated devices are used to operate via remote location.
Abstract: loss of feedwater accident is one of the frequently sever accidents in steam boiler facilities. It threatens the system structural integrity and generates serious hazards and economic loses. The safety analysis of the thermal installations, based extensively on the numeric simulation. The simulation analysis using realistic computer codes like Relap5/Mod3.2 will help understand steam boiler thermal-hydraulic behavior during normal and abnormal conditions. In this study, we are interested on the evaluation of the radiant steam boiler assessment and response to loss-of-feedwater accident. Pressure, temperature and flow rate profiles are presented in various steam boiler system components. The obtained results demonstrate the importance and capability of the Relap5/Mod3.2 code in the thermal-hydraulic analysis of the steam boiler facilities.
Abstract: This paper presents a new methodology to select test
cases from regression test suites. The selection strategy is based on
analyzing the dynamic behavior of the applications that written in
any programming language. Methods based on dynamic analysis are
more safe and efficient. We design a technique that combine the code
based technique and model based technique, to allow comparing the
object oriented of an application that written in any programming
language. We have developed a prototype tool that detect changes
and select test cases from test suite.
Abstract: Blind Signature were introduced by Chaum. In this
scheme, a signer can “sign” a document without knowing the
document contain. This is particularly important in electronic voting.
CryptO-0N2 is an electronic voting protocol which is development of
CryptO-0N. During its development this protocol has not been
furnished with the requirement of blind signature, so the choice of
voters can be determined by counting center. In this paper will be
presented of implementation of blind signature using RSA algorithm.
Abstract: Embedding Sustainability in technological curricula has become a crucial factor for educating engineers with competences in sustainability. The Technical University of Catalonia UPC, in 2008, designed the Sustainable Technology Excellence Program STEP 2015 in order to assure a successful Sustainability Embedding. This Program takes advantage of the opportunity that the redesign of all Bachelor and Master Degrees in Spain by 2010 under the European Higher Education Area framework offered. The STEP program goals are: to design compulsory courses in each degree; to develop the conceptual base and identify reference models in sustainability for all specialties at UPC; to create an internal interdisciplinary network of faculty from all the schools; to initiate new transdisciplinary research activities in technology-sustainability-education; to spread the know/how attained; to achieve international scientific excellence in technology-sustainability-education and to graduate the first engineers/architects of the new EHEA bachelors with sustainability as a generic competence. Specifically, in this paper authors explain their experience in leading the STEP program, and two examples are presented: Industrial Robotics subject and the curriculum for the School of Architecture.
Abstract: There are several approaches in trying to solve the
Quantitative 1Structure-Activity Relationship (QSAR) problem.
These approaches are based either on statistical methods or on
predictive data mining. Among the statistical methods, one should
consider regression analysis, pattern recognition (such as cluster
analysis, factor analysis and principal components analysis) or partial
least squares. Predictive data mining techniques use either neural
networks, or genetic programming, or neuro-fuzzy knowledge. These
approaches have a low explanatory capability or non at all. This
paper attempts to establish a new approach in solving QSAR
problems using descriptive data mining. This way, the relationship
between the chemical properties and the activity of a substance
would be comprehensibly modeled.
Abstract: In this research, a systematic investigation was carried out to determine the optimum conditions of HDS reactor. Moreover, a suitable model was developed for a rigorous RTO (real time optimization) loop of HDS (Hydro desulfurization) process. A systematic experimental series was designed based on CCD (Central Composite design) and carried out in the related pilot plant to tune the develop model. The designed variables in the experiments were Temperature, LHSV and pressure. However, the hydrogen over fresh feed ratio was remained constant. The ranges of these variables were respectively equal to 320-380ºC, 1- 21/hr and 50-55 bar. a power law kinetic model was also developed for our further research in the future .The rate order and activation energy , power of reactant concentration and frequency factor of this model was respectively equal to 1.4, 92.66 kJ/mol and k0=2.7*109 .
Abstract: Benchmarking cleaner production performance is an
effective way of pollution control and emission reduction in coal-fired
power industry. A benchmarking method using two-stage
super-efficiency data envelopment analysis for coal-fired power plants
is proposed – firstly, to improve the cleaner production performance of
DEA-inefficient or weakly DEA-efficient plants, then to select the
benchmark from performance-improved power plants. An empirical
study is carried out with the survey data of 24 coal-fired power plants.
The result shows that in the first stage the performance of 16 plants is
DEA-efficient and that of 8 plants is relatively inefficient. The target
values for improving DEA-inefficient plants are acquired by
projection analysis. The efficient performance of 24 power plants and
the benchmarking plant is achieved in the second stage. The two-stage
benchmarking method is practical to select the optimal benchmark in
the cleaner production of coal-fired power industry and will
continuously improve plants- cleaner production performance.
Abstract: The objective of this work was to investigate flow
properties of powdered infant formula samples. Samples were
purchased at a local pharmacy and differed in composition. Lactose
free infant formula, gluten free infant formula and infant formulas
containing dietary fibers and probiotics were tested and compared
with a regular infant formula sample which did not contain any of
these supplements. Particle size and bulk density were determined
and their influence on flow properties was discussed. There were no
significant differences in bulk densities of the samples, therefore the
connection between flow properties and bulk density could not be
determined. Lactose free infant formula showed flow properties
different to standard supplement-free sample. Gluten free infant
formula with addition of probiotic microorganisms and dietary fiber
had the narrowest particle size distribution range and exhibited the
best flow properties. All the other samples exhibited the same
tendency of decreasing compaction coefficient with increasing flow
speed, which means they all become freer flowing with higher flow
speeds.
Abstract: Many real-world data sets consist of a very high dimensional feature space. Most clustering techniques use the distance or similarity between objects as a measure to build clusters. But in high dimensional spaces, distances between points become relatively uniform. In such cases, density based approaches may give better results. Subspace Clustering algorithms automatically identify lower dimensional subspaces of the higher dimensional feature space in which clusters exist. In this paper, we propose a new clustering algorithm, ISC – Intelligent Subspace Clustering, which tries to overcome three major limitations of the existing state-of-art techniques. ISC determines the input parameter such as є – distance at various levels of Subspace Clustering which helps in finding meaningful clusters. The uniform parameters approach is not suitable for different kind of databases. ISC implements dynamic and adaptive determination of Meaningful clustering parameters based on hierarchical filtering approach. Third and most important feature of ISC is the ability of incremental learning and dynamic inclusion and exclusions of subspaces which lead to better cluster formation.
Abstract: Paced Auditory Serial Addition Test (PASAT) has
been used as a common research tool for different neurological
disorders like Multiple Sclerosis. Recently, technology let
researchers to introduce a new versions of the visual test, the paced
visual serial addition test (PVSAT). In this paper, the computerized
version of these two tests is introduced. Beside the number of true
responses are interpreted, the reaction time of subjects are calculated
by the software. We hypothesize that paying attention to the reaction
time may be valuable. For this purpose, sixty eight female normal
subjects and fifty eight male normal subjects are enrolled in the
study. We investigate the similarity between the PASAT3 and
PVSAT3 in number of true responses and the new criterion (the
average reaction time of each subject). The similarity between two
tests were rejected (p-value = 0.000) which means that these two test
differ. The effect of sex in the tests were not approved since the pvalues
of different between PASAT3 and PVSAT3 in both sex is the
same (p-value = 0.000) which means that male and female subjects
performed the tests at no different level of performance. The new
criterion shows a negative correlation with the age which offers aged
normal subjects may have the same number of true responses as the
young subjects but they have latent responses. This will give prove
for the importance of reaction time.
Abstract: The noteworthy point in the advancement of Brain Machine Interface (BMI) research is the ability to accurately extract features of the brain signals and to classify them into targeted control action with the easiest procedures since the expected beneficiaries are of disabled. In this paper, a new feature extraction method using the combination of adaptive band pass filters and adaptive autoregressive (AAR) modelling is proposed and applied to the classification of right and left motor imagery signals extracted from the brain. The introduction of the adaptive bandpass filter improves the characterization process of the autocorrelation functions of the AAR models, as it enhances and strengthens the EEG signal, which is noisy and stochastic in nature. The experimental results on the Graz BCI data set have shown that by implementing the proposed feature extraction method, a LDA and SVM classifier outperforms other AAR approaches of the BCI 2003 competition in terms of the mutual information, the competition criterion, or misclassification rate.
Abstract: Prickly pear (Opuntia spp) fruit has received renewed
interest since it contains a betalain pigment that has an attractive
purple colour for the production of juice. Prickly pear juice was
prepared by homogenizing the fruit and treating the pulp with 48 g of
pectinase from Aspergillus niger. Titratable acidity was determined
by diluting 10 ml prickly pear juice with 90 ml deionized water and
titrating to pH 8.2 with 0.1 N NaOH. Brix was measured using a
refractometer and ascorbic acid content assayed
spectrophotometrically. Colour variation was determined
colorimetrically (Hunter L.a.b.). Hunter L.a.b. analysis showed that
the red purple colour of prickly pear juice had been affected by juice
treatments. This was indicated by low light values of colour
difference meter (CDML*), hue, CDMa* and CDMb* values. It was
observed that non-treated prickly pear juice had a high (colour
difference meter of light) CDML* of 3.9 compared to juice
treatments (range 3.29 to 2.14). The CDML* significantly (p