Abstract: The building sector is responsible, in many
industrialized countries, for about 40% of the total energy
requirements, so it seems necessary to devote some efforts in this
area in order to achieve a significant reduction of energy
consumption and of greenhouse gases emissions.
The paper presents a study aiming at providing a design
methodology able to identify the best configuration of the system
building/plant, from a technical, economic and environmentally point
of view.
Normally, the classical approach involves a building's energy
loads analysis under steady state conditions, and subsequent selection
of measures aimed at improving the energy performance, based on
previous experience made by architects and engineers in the design
team. Instead, the proposed approach uses a sequence of two wellknown
scientifically validated calculation methods (TRNSYS and
RETScreen), that allow quite a detailed feasibility analysis.
To assess the validity of the calculation model, an existing,
historical building in Central Italy, that will be the object of
restoration and preservative redevelopment, was selected as a casestudy.
The building is made of a basement and three floors, with a
total floor area of about 3,000 square meters.
The first step has been the determination of the heating and
cooling energy loads of the building in a dynamic regime by means,
which allows simulating the real energy needs of the building in
function of its use. Traditional methodologies, based as they are on
steady-state conditions, cannot faithfully reproduce the effects of
varying climatic conditions and of inertial properties of the structure.
With this model is possible to obtain quite accurate and reliable
results that allow identifying effective combinations building-HVAC
system.
The second step has consisted of using output data obtained as
input to the calculation model, which enables to compare different
system configurations from the energy, environmental and financial
point of view, with an analysis of investment, and operation and
maintenance costs, so allowing determining the economic benefit of
possible interventions.
The classical methodology often leads to the choice of
conventional plant systems, while our calculation model provides a
financial-economic assessment for innovative energy systems and
low environmental impact.
Computational analysis can help in the design phase, particularly
in the case of complex structures with centralized plant systems, by
comparing the data returned by the calculation model for different
design options.
Abstract: Pulmonary Function Tests are important non-invasive
diagnostic tests to assess respiratory impairments and provides
quantifiable measures of lung function. Spirometry is the most
frequently used measure of lung function and plays an essential role
in the diagnosis and management of pulmonary diseases. However,
the test requires considerable patient effort and cooperation,
markedly related to the age of patients resulting in incomplete data
sets. This paper presents, a nonlinear model built using Multivariate
adaptive regression splines and Random forest regression model to
predict the missing spirometric features. Random forest based feature
selection is used to enhance both the generalization capability and the
model interpretability. In the present study, flow-volume data are
recorded for N= 198 subjects. The ranked order of feature importance
index calculated by the random forests model shows that the
spirometric features FVC, FEF25, PEF, FEF25-75, FEF50 and the
demographic parameter height are the important descriptors. A
comparison of performance assessment of both models prove that, the
prediction ability of MARS with the `top two ranked features namely
the FVC and FEF25 is higher, yielding a model fit of R2= 0.96 and
R2= 0.99 for normal and abnormal subjects. The Root Mean Square
Error analysis of the RF model and the MARS model also shows that
the latter is capable of predicting the missing values of FEV1 with a
notably lower error value of 0.0191 (normal subjects) and 0.0106
(abnormal subjects) with the aforementioned input features. It is
concluded that combining feature selection with a prediction model
provides a minimum subset of predominant features to train the
model, as well as yielding better prediction performance. This
analysis can assist clinicians with a intelligence support system in the
medical diagnosis and improvement of clinical care.
Abstract: In this paper, the problem of fault detection and
isolation in the attitude control subsystem of spacecraft formation
flying is considered. In order to design the fault detection method, an
extended Kalman filter is utilized which is a nonlinear stochastic state
estimation method. Three fault detection architectures, namely,
centralized, decentralized, and semi-decentralized are designed based
on the extended Kalman filters. Moreover, the residual generation
and threshold selection techniques are proposed for these
architectures.
Abstract: Fungal mutant strains have produced cellulase and
xylanase enzymes, and have induced high hydrolysis with enhanced
of rice straw. The mutants were obtained by exposing Penicillium
strain to UV-light treatments. Screening and selection after treatment
with UV-light were carried out using cellulolytic and xylanolytic
clear zones method to select the hypercellulolytic and
hyperxylanolytic mutants. These mutants were evaluated for their
cellulase and xylanase enzyme production as well as their abilities for
biodegradation of rice straw. The mutant 12 UV/1 produced 306.21%
and 209.91% cellulase and xylanase, respectively, as compared with
the original wild type strain. This mutant showed high capacity of
rice straw degradation. The effectiveness of tested mutant strain and
that of wild strain was compared in relation to enhancing the
composting process of rice straw and animal manures mixture. The
results obtained showed that the compost product of inoculated
mixture with mutant strain (12 UV/1) was the best compared to the
wild strain and un-inoculated mixture. Analysis of the composted
materials showed that the characteristics of the produced compost
were close to those of the high quality standard compost. The results
obtained in the present work suggest that the combination between
rice straw and animal manure could be used for enhancing the
composting process of rice straw and particularly when applied with
fungal decomposer accelerating the composting process.
Abstract: The aim of this work is to build a model based on
tissue characterization that is able to discriminate pathological and
non-pathological regions from three-phasic CT images. With our
research and based on a feature selection in different phases, we are
trying to design a neural network system with an optimal neuron
number in a hidden layer. Our approach consists of three steps:
feature selection, feature reduction, and classification. For each
region of interest (ROI), 6 distinct sets of texture features are
extracted such as: first order histogram parameters, absolute gradient,
run-length matrix, co-occurrence matrix, autoregressive model, and
wavelet, for a total of 270 texture features. When analyzing more
phases, we show that the injection of liquid cause changes to the high
relevant features in each region. Our results demonstrate that for
detecting HCC tumor phase 3 is the best one in most of the features
that we apply to the classification algorithm. The percentage of
detection between pathology and healthy classes, according to our
method, relates to first order histogram parameters with accuracy of
85% in phase 1, 95% in phase 2, and 95% in phase 3.
Abstract: The wide use of the Internet-based applications bring many challenges to the researchers to guarantee the continuity of the connections needed by the mobile hosts and provide reliable Internet access for them. One of proposed solutions by Internet Engineering Task Force (IETF) is to connect the local, multi-hop, and infrastructure-less Mobile Ad hoc Network (MANET) with Internet structure. This connection is done through multi-interface devices known as Internet Gateways. Many issues are related to this connection like gateway discovery, handoff, address auto-configuration and selecting the optimum gateway when multiple gateways exist. Many studies were done proposing gateway selection schemes with a single selection criterion or weighted multiple criteria. In this research, a review of some of these schemes is done showing the differences, the features, the challenges and the drawbacks of each of them.
Abstract: Conservation works in Malaysia that is procured by
public organisation usually follow the traditional approach where the
works are tendered based on Bills of Quantities (BQ). One of the
purposes of tendering is to enable the selection of a competent
contractor that offers a competitive price. While competency of the
contractors are assessed by their technical knowledge, experience and
track records, the assessment of pricing will be dependent on the
tender amount. However, the issue currently faced by the
conservation works sector is the difficulty in assessing the
competitiveness and reasonableness of the tender amount due to the
high variance between the tenders amount. Thus, this paper discusses
the factors that cause difficulty to the tenderers in pricing
competitively in a bidding exercise for conservation tenders. Data on
tendering is collected from interviews with conservation works
contractors to gain in-depth understanding of the barriers faced in
pricing tenders of conservation works. Findings from the study lent
support to the contention that the variance of tender amount is very
high amongst tenderers. The factors identified in the survey are the
format of BQ, hidden works, experience and labour and material
costs.
Abstract: Various personality profile tests are used to identify
personality strengths and limits in individuals, helping both
individuals and managers to optimize work and team effort in
organizations. One such test, the Hartman’s personality profile,
emphasizes four driving "core motives" influenced or affected by
both strengths and limitations classified into four colors: Red -
motivated by power; Blue - discipline and loyalty; White - peace; and
Yellow – fun loving. Two shortcomings of Hartman’s personality test
are noted; 1) only one selection for every item / situation allowed and
2) selection of an item / option even if not applicable. A test taker
may be as much nurturing as he is opinionated but since
“opinionated” seems less attractive the individual would likely select
nurturing, causing a misidentification in personality strengths and
limits. Since few individuals have a “strong” personality, it is
difficult to assess their true personality strengths and limits allowing
only one choice or requiring unwanted choices, undermining the
potential of the test. We modified Hartman’s personality profile
allowing test takers to make either multiple choices for any item /
situation or leave them blank if applicable. Sixty-eight participants
(38 males and 30 females), 17 - 49 years old, from countries in Asia,
Europe, N. America, CIS, Africa, Latin America, and Oceania were
included. 58 participants (85.3%) reported the modified test, allowing
multiple / no choices better identified their personality strengths and
limits, while 10 participants (14.7%) expressed the original (one
choice version) was sufficient. The overall results show that our
modified test enhanced the identification and balance of core
personalities’ strengths and limits, aiding test takers, managers and
organizations to better assess individual characteristics, particularly
useful in making task-related, teamwork, and management decisions.
Abstract: The aim of this study was to select the best strains of
Saccharomyces cerevisiae able to resist lead and cadmium. Ten
strains were screened on the basis of their resistance at different
concentrations of 0, 2, 4, 8, 12, 16, 20 and 24 ppm for Pb and 0, 0.5,
1, 2, 4, 6, 8 and 10 ppm for Cd. The properties of baker's yeast
quality were decreased by the increase of Pb or Cd in growth
medium. The slope values of yield, total viable cells and gassing
power of produced baker's yeast were investigated as an indicator of
metal resistant. In addition, concentrations of Pb and Cd in produced
baker's yeast were determined. The strain of S. cerevisiae FH-620
had the highest resistance against Pb and Cd and had the minimum
levels of both two investigated metals in produced baker's yeast.
Abstract: The web’s increased popularity has included a huge
amount of information, due to which automated web page
classification systems are essential to improve search engines’
performance. Web pages have many features like HTML or XML
tags, hyperlinks, URLs and text contents which can be considered
during an automated classification process. It is known that Webpage
classification is enhanced by hyperlinks as it reflects Web page
linkages. The aim of this study is to reduce the number of features to
be used to improve the accuracy of the classification of web pages. In
this paper, a novel feature selection method using an improved
Particle Swarm Optimization (PSO) using principle of evolution is
proposed. The extracted features were tested on the WebKB dataset
using a parallel Neural Network to reduce the computational cost.
Abstract: Every machine plays roles of client and server
simultaneously in a peer-to-peer (P2P) network. Though a P2P
network has many advantages over traditional client-server models
regarding efficiency and fault-tolerance, it also faces additional
security threats. Users/IT administrators should be aware of risks
from malicious code propagation, downloaded content legality, and
P2P software’s vulnerabilities. Security and preventative measures
are a must to protect networks from potential sensitive information
leakage and security breaches. Bit Torrent is a popular and scalable
P2P file distribution mechanism which successfully distributes large
files quickly and efficiently without problems for origin server. Bit
Torrent achieved excellent upload utilization according to
measurement studies, but it also raised many questions as regards
utilization in settings, than those measuring, fairness, and Bit
Torrent’s mechanisms choice. This work proposed a block selection
technique using Fuzzy ACO with optimal rules selected using ACO.
Abstract: Neurons in the nervous system communicate with
each other by producing electrical signals called spikes. To
investigate the physiological function of nervous system it is essential
to study the activity of neurons by detecting and sorting spikes in the
recorded signal. In this paper a method is proposed for considering
the spike sorting problem which is based on the nonlinear modeling
of spikes using exponential autoregressive model. The genetic
algorithm is utilized for model parameter estimation. In this regard
some selected model coefficients are used as features for sorting
purposes. For optimal selection of model coefficients, self-organizing
feature map is used. The results show that modeling of spikes with
nonlinear autoregressive model outperforms its linear counterpart.
Also the extracted features based on the coefficients of exponential
autoregressive model are better than wavelet based extracted features
and get more compact and well-separated clusters. In the case of
spikes different in small-scale structures where principal component
analysis fails to get separated clouds in the feature space, the
proposed method can obtain well-separated cluster which removes
the necessity of applying complex classifiers.
Abstract: Analyzing DNA microarray data sets is a great
challenge, which faces the bioinformaticians due to the complication
of using statistical and machine learning techniques. The challenge
will be doubled if the microarray data sets contain missing data,
which happens regularly because these techniques cannot deal with
missing data. One of the most important data analysis process on
the microarray data set is feature selection. This process finds the
most important genes that affect certain disease. In this paper, we
introduce a technique for imputing the missing data in microarray
data sets while performing feature selection.
Abstract: Iris codes contain bits with different entropy. This
work investigates different strategies to reduce the size of iris
code templates with the aim of reducing storage requirements and
computational demand in the matching process. Besides simple subsampling
schemes, also a binary multi-resolution representation as
used in the JBIG hierarchical coding mode is assessed. We find that
iris code template size can be reduced significantly while maintaining
recognition accuracy. Besides, we propose a two-stage identification
approach, using small-sized iris code templates in a pre-selection
stage, and full resolution templates for final identification, which
shows promising recognition behaviour.
Abstract: The number of Ground Motion Prediction Equations
(GMPEs) used for predicting peak ground acceleration (PGA) and
the number of earthquake recordings that have been used for fitting
these equations has increased in the past decades. The current PF-L
database contains 3550 recordings. Since the GMPEs frequently
model the peak ground acceleration the goal of the present study was
to refit a selection of 44 of the existing equation models for PGA in
light of the latest data. The algorithm Levenberg-Marquardt was used
for fitting the coefficients of the equations and the results are
evaluated both quantitatively by presenting the root mean squared
error (RMSE) and qualitatively by drawing graphs of the five best
fitted equations. The RMSE was found to be as low as 0.08 for the
best equation models. The newly estimated coefficients vary from the
values published in the original works.
Abstract: Chemotherapy and radiotherapy are one of the major
treatment modalities that play important role in the management of a
number of different cancers. This study for the first time evaluates the
toxicity of these treatment modalities and its impact on quality of life
of cancer patients in Pakistan. The study also for the first time
determines what cancer patients of different ages and cancer stages
believe would be an effective intervention to manage their
psychosocial needs and treatment induced toxicity. The article also
provides evidence based approach for the use of variety of
interventions to mange cancer treatment induced morbidity and
toxicity. In light of the present study and reviewed research data,
evidence based recommendations are also made for selection of
appropriate interventions to manage Pain, Nausea and Vomiting,
Anxiety and Depression, Fatigue and Overall QOL of cancer
survivors.
Abstract: The aim of this work was to apply extractive
distillation for acetonitrile removal from water solutions, to validate
thermodynamic criterion based on excess Gibbs energy to entrainer
selection process for acetonitrile – water mixture separation and show
its potential efficiency at isothermal conditions as well as at isobaric
(conditions of real distillation process), to simulate and analyze an
extractive distillation process with chosen entrainers: optimize
amount of trays and feeds, entrainer/original mixture and reflux
ratios. Equimolar composition of the feed stream was chosen for the
process, comparison of the energy consumptions was carried out.
Glycerol was suggested as the most energetically and ecologically
suitable entrainer.
Abstract: Contracting authorities in the public sector are
obligated to apply the principles provided for in the Polish law for the
evaluation and selection of contractors. In order to analyse the
methods of contractors selecting applied in practice by public clients,
the notices of contract award results for construction works were
analysed. The analysis shows that the procedure selected more and
more often is open competitive bidding, where the assessment of the
competence of contractors is not very precise, as well as noncompetitive
bidding, i.e. single source procurement. The share of
procurement procedures, where the only criterion is price, is
increasing. The solution to the problems existing here might be the
introduction of one of the forms of pre-selection of contractors. The
article also briefly discusses verification systems for companies
applying for public contracts used in EU countries.
Abstract: This paper describes a novel application of Fiber
Braggs Grating (FBG) sensors in the assessment of human postural
stability and balance on an unstable platform. In this work, FBG
sensor Stability Analyzing Device (FBGSAD) is developed for
measurement of plantar strain to assess the postural stability of
subjects on unstable platforms during different stances in eyes open
and eyes closed conditions on a rocker board. The studies are
validated by comparing the Centre of Gravity (CG) variations
measured on the lumbar vertebra of subjects using a commercial
accelerometer. The results obtained from the developed FBGSAD
depict qualitative similarities with the data recorded by commercial
accelerometer. The advantage of the FBGSAD is that it measures
simultaneously plantar strain distribution and postural stability of the
subject along with its inherent benefits like non-requirement of
energizing voltage to the sensor, electromagnetic immunity and
simple design which suits its applicability in biomechanical
applications. The developed FBGSAD can serve as a tool/yardstick to
mitigate space motion sickness, identify individuals who are
susceptible to falls and to qualify subjects for balance and stability,
which are important factors in the selection of certain unique
professionals such as aircraft pilots, astronauts, cosmonauts etc.
Abstract: Several of the practical industrial control processes are
multivariable processes. Due to the relation amid the variables
(interaction), delay in the loops, it is very intricate to design a
controller directly for these processes. So first, the interaction of the
variables is analyzed using Relative Normalized Gain Array
(RNGA), which considers the time constant, static gain and delay
time of the processes. Based on the effect of RNGA, relative gain
array (RGA) and NI, the pair (control configuration) of variables to
be controlled by decentralized control is selected. The equivalent
transfer function (ETF) of the process model is estimated as first
order process with delay using the corresponding elements in the
Relative gain array and Relative average residence time array
(RARTA) of the processes. Secondly, a decentralized Proportional-
Integral (PI) controller is designed for each ETF simply using
frequency response specifications. Finally, the performance and
robustness of the algorithm is comparing with existing related
approaches to validate the effectiveness of the projected algorithm.