Abstract: Nanophotocatalysts such as titanium (TiO2), zinc (ZnO), and iron (Fe2O3) oxides can be used in organic pollutants oxidation, and in many other applications. But among the challenges for technological application (scale-up) of the nanotechnology scientific developments two aspects are still little explored: research on environmental risk of the nanomaterials preparation methods, and the study of nanomaterials properties and/or performance variability. The environmental analysis was performed for six different methods of ZnO nanoparticles synthesis, and showed that it is possible to identify the more environmentally compatible process even at laboratory scale research. The obtained ZnO nanoparticles were tested as photocatalysts, and increased the degradation rate of the Rhodamine B dye up to 30 times.
Abstract: “Web of Trust" is one of the recognized goals for
Web 2.0. It aims to make it possible for the people to take
responsibility for what they publish on the web, including
organizations, businesses and individual users. These objectives,
among others, drive most of the technologies and protocols recently
standardized by the governing bodies. One of the great advantages of
Web infrastructure is decentralization of publication. The primary
motivation behind Web 2.0 is to assist the people to add contents for
Collective Intelligence (CI) while providing mechanisms to link
content with people for evaluations and accountability of
information. Such structure of contents will interconnect users and
contents so that users can use contents to find participants and vice
versa. This paper proposes conceptual information storage and
linking model, based on decentralized information structure, that
links contents and people together. The model uses FOAF, Atom,
RDF and RDFS and can be used as a blueprint to develop Web 2.0
applications for any e-domain. However, primary target for this
paper is online trust evaluation domain. The proposed model targets
to assist the individuals to establish “Web of Trust" in online trust
domain.
Abstract: The performance and complexity of QoS routing depends on the complex interaction between a large set of parameters. This paper investigated the scaling properties of source-directed link-state routing in large core networks. The simulation results show that the routing algorithm, network topology, and link cost function each have a significant impact on the probability of successfully routing new connections. The experiments confirm and extend the findings of other studies, and also lend new insight designing efficient quality-of-service routing policies in large networks.
Abstract: Iterative learning control aims to achieve zero tracking
error of a specific command. This is accomplished by iteratively
adjusting the command given to a feedback control system, based on
the tracking error observed in the previous iteration. One would like
the iterations to converge to zero tracking error in spite of any error
present in the model used to design the learning law. First, this need
for stability robustness is discussed, and then the need for robustness
of the property that the transients are well behaved. Methods of
producing the needed robustness to parameter variations and to
singular perturbations are presented. Then a method involving
reverse time runs is given that lets the world behavior produce the
ILC gains in such a way as to eliminate the need for a mathematical
model. Since the real world is producing the gains, there is no issue
of model error. Provided the world behaves linearly, the approach
gives an ILC law with both stability robustness and good transient
robustness, without the need to generate a model.
Abstract: This paper presents an intrusion detection system of hybrid neural network model based on RBF and Elman. It is used for anomaly detection and misuse detection. This model has the memory function .It can detect discrete and related aggressive behavior effectively. RBF network is a real-time pattern classifier, and Elman network achieves the memory ability for former event. Based on the hybrid model intrusion detection system uses DARPA data set to do test evaluation. It uses ROC curve to display the test result intuitively. After the experiment it proves this hybrid model intrusion detection system can effectively improve the detection rate, and reduce the rate of false alarm and fail.
Abstract: The purpose of this article applies the monthly final
energy yield and failure data of 202 PV systems installed in Taiwan to
analyze the PV operational performance and system availability. This
data is collected by Industrial Technology Research Institute through
manual records. Bad data detection and failure data estimation
approaches are proposed to guarantee the quality of the received
information. The performance ratio value and system availability are
then calculated and compared with those of other countries. It is
indicated that the average performance ratio of Taiwan-s PV systems
is 0.74 and the availability is 95.7%. These results are similar with
those of Germany, Switzerland, Italy and Japan.
Abstract: The biomarker for colorectal cancer (CRC) is CEACAM-6 antigen (C6AG). Therefore, this study aims to develop a novel, simple and low-cost CEACAM-6 antigen immumosensor (C6AG-IMS), based on electrical impedance measurement, for precise determination of C6AG. A low-cost screen-printed graphite electrode was constructed and used as the sensor, with CEACAM-6 antibody (C6AB) immobilized on it. The procedures of sensor fabrication and antibody immobilization are simple and low-cost. Measurement of the electrical impedance at a definite frequency ranges (0.43 – 1.26 MHz) showed that the C6AG-IMS has an excellent linear (r2>0.9) response range (8.125 – 65 pg/mL), covering the normal physiological and pathological ranges of blood C6AG levels. Also, the C6AG-IMS has excellent reliability and validity, with the intraclass correlation coefficient being 0.97. In conclusion, a novel, simple, low-cost and reliable C6AG-IMS was designed and developed, being able to accurately determine blood C6AG levels in the range of pathological and normal physiological regions. The C6AG-IMS can provide a point-of-care and immediate screening results to the user at home.
Abstract: The hydrogen peroxide treatment was able to
remediate chlorophenols, polycyclic aromatic hydrocarbons, diesel
and transformer oil contaminated soil. Chemical treatment of
contaminants adsorbed in peat resulted in lower contaminants-
removal and required higher addition of chemicals than the treatment
of contaminants in sand. The hydrogen peroxide treatment was found
to be feasible for soil remediation at natural soil pH. Contaminants in
soil could degrade with the addition of hydrogen peroxide only
indicating the ability of transition metals ions and minerals of these
metals presented in soil to catalyse the reaction of hydrogen peroxide
decomposition.
Abstract: Sickness absence represents a major economic and
social issue. Analysis of sick leave data is a recurrent challenge to analysts because of the complexity of the data structure which is
often time dependent, highly skewed and clumped at zero. Ignoring these features to make statistical inference is likely to be inefficient
and misguided. Traditional approaches do not address these problems. In this study, we discuss model methodologies in terms of statistical techniques for addressing the difficulties with sick leave data. We also introduce and demonstrate a new method by performing a longitudinal assessment of long-term absenteeism using
a large registration dataset as a working example available from the Helsinki Health Study for municipal employees from Finland during the period of 1990-1999. We present a comparative study on model
selection and a critical analysis of the temporal trends, the occurrence
and degree of long-term sickness absences among municipal employees. The strengths of this working example include the large
sample size over a long follow-up period providing strong evidence in supporting of the new model. Our main goal is to propose a way to
select an appropriate model and to introduce a new methodology for analysing sickness absence data as well as to demonstrate model
applicability to complicated longitudinal data.
Abstract: This paper proposes a smart design strategy for a sequential detector to reliably detect the primary user-s signal, especially in fast fading environments. We study the computation of the log-likelihood ratio for coping with a fast changing received signal and noise sample variances, which are considered random variables. First, we analyze the detectability of the conventional generalized log-likelihood ratio (GLLR) scheme when considering fast changing statistics of unknown parameters caused by fast fading effects. Secondly, we propose an efficient sensing algorithm for performing the sequential probability ratio test in a robust and efficient manner when the channel statistics are unknown. Finally, the proposed scheme is compared to the conventional method with simulation results with respect to the average number of samples required to reach a detection decision.
Abstract: Metal stamping die design is a complex, experiencebased
and time-consuming task. Various artificial intelligence (AI)
techniques are being used by worldwide researchers for stamping die
design to reduce complexity, dependence on human expertise and
time taken in design process as well as to improve design efficiency.
In this paper a comprehensive review of applications of AI
techniques in manufacturability evaluation of sheet metal parts, die
design and process planning of metal stamping die is presented.
Further the salient features of major research work published in the
area of metal stamping are presented in tabular form and scope of
future research work is identified.
Abstract: An advanced Monte Carlo simulation method, called Subset Simulation (SS) for the time-dependent reliability prediction for underground pipelines has been presented in this paper. The SS can provide better resolution for low failure probability level with efficient investigating of rare failure events which are commonly encountered in pipeline engineering applications. In SS method, random samples leading to progressive failure are generated efficiently and used for computing probabilistic performance by statistical variables. SS gains its efficiency as small probability event as a product of a sequence of intermediate events with larger conditional probabilities. The efficiency of SS has been demonstrated by numerical studies and attention in this work is devoted to scrutinise the robustness of the SS application in pipe reliability assessment. It is hoped that the development work can promote the use of SS tools for uncertainty propagation in the decision-making process of underground pipelines network reliability prediction.
Abstract: This study presents a systematic analysis of the
dynamic behaviors of a gear-bearing system with porous squeeze film
damper (PSFD) under nonlinear suspension, nonlinear oil-film force
and nonlinear gear meshing force effect. It can be found that the
system exhibits very rich forms of sub-harmonic and even the chaotic
vibrations. The bifurcation diagrams also reveal that greater values of
permeability may not only improve non-periodic motions effectively,
but also suppress dynamic amplitudes of the system. Therefore, porous
effect plays an important role to improve dynamic stability of
gear-bearing systems or other mechanical systems. The results
presented in this study provide some useful insights into the design
and development of a gear-bearing system for rotating machinery that
operates in highly rotational speed and highly nonlinear regimes.
Abstract: Software reliability prediction gives a great opportunity to measure the software failure rate at any point throughout system test. A software reliability prediction model provides with the technique for improving reliability. Software reliability is very important factor for estimating overall system reliability, which depends on the individual component reliabilities. It differs from hardware reliability in that it reflects the design perfection. Main reason of software reliability problems is high complexity of software. Various approaches can be used to improve the reliability of software. We focus on software reliability model in this article, assuming that there is a time redundancy, the value of which (the number of repeated transmission of basic blocks) can be an optimization parameter. We consider given mathematical model in the assumption that in the system may occur not only irreversible failures, but also a failure that can be taken as self-repairing failures that significantly affect the reliability and accuracy of information transfer. Main task of the given paper is to find a time distribution function (DF) of instructions sequence transmission, which consists of random number of basic blocks. We consider the system software unreliable; the time between adjacent failures has exponential distribution.
Abstract: The world economic crises and budget constraints
have caused authorities, especially those in developing countries, to
rationalize water quality monitoring activities. Rationalization
consists of reducing the number of monitoring sites, the number of
samples, and/or the number of water quality variables measured. The
reduction in water quality variables is usually based on correlation. If
two variables exhibit high correlation, it is an indication that some of
the information produced may be redundant. Consequently, one
variable can be discontinued, and the other continues to be measured.
Later, the ordinary least squares (OLS) regression technique is
employed to reconstitute information about discontinued variable by
using the continuously measured one as an explanatory variable. In
this paper, two record extension techniques are employed to
reconstitute information about discontinued water quality variables,
the OLS and the Line of Organic Correlation (LOC). An empirical
experiment is conducted using water quality records from the Nile
Delta water quality monitoring network in Egypt. The record
extension techniques are compared for their ability to predict
different statistical parameters of the discontinued variables. Results
show that the OLS is better at estimating individual water quality
records. However, results indicate an underestimation of the variance
in the extended records. The LOC technique is superior in preserving
characteristics of the entire distribution and avoids underestimation
of the variance. It is concluded from this study that the OLS can be
used for the substitution of missing values, while LOC is preferable
for inferring statements about the probability distribution.
Abstract: According to the statistics, the prevalence of congenital hearing loss in Taiwan is approximately six thousandths; furthermore, one thousandths of infants have severe hearing impairment. Hearing ability during infancy has significant impact in the development of children-s oral expressions, language maturity, cognitive performance, education ability and social behaviors in the future. Although most children born with hearing impairment have sensorineural hearing loss, almost every child more or less still retains some residual hearing. If provided with a hearing aid or cochlear implant (a bionic ear) timely in addition to hearing speech training, even severely hearing-impaired children can still learn to talk. On the other hand, those who failed to be diagnosed and thus unable to begin hearing and speech rehabilitations on a timely manner might lose an important opportunity to live a complete and healthy life. Eventually, the lack of hearing and speaking ability will affect the development of both mental and physical functions, intelligence, and social adaptability. Not only will this problem result in an irreparable regret to the hearing-impaired child for the life time, but also create a heavy burden for the family and society. Therefore, it is necessary to establish a set of computer-assisted predictive model that can accurately detect and help diagnose newborn hearing loss so that early interventions can be provided timely to eliminate waste of medical resources. This study uses information from the neonatal database of the case hospital as the subjects, adopting two different analysis methods of using support vector machine (SVM) for model predictions and using logistic regression to conduct factor screening prior to model predictions in SVM to examine the results. The results indicate that prediction accuracy is as high as 96.43% when the factors are screened and selected through logistic regression. Hence, the model constructed in this study will have real help in clinical diagnosis for the physicians and actually beneficial to the early interventions of newborn hearing impairment.
Abstract: This paper presents reliability evaluation techniques
which are applied in distribution system planning studies and
operation. Reliability of distribution systems is an important issue in
power engineering for both utilities and customers. Reliability is a
key issue in the design and operation of electric power distribution
systems and load. Reliability evaluation of distribution systems has
been the subject of many recent papers and the modeling and
evaluation techniques have improved considerably.
Abstract: The study was designed to develop a measurement of
the positive emotion regulation questionnaire (PERQ) that assesses
positive emotion regulation strategies through self-report. The 14
items developed for the surveying instrument of the study were based
upon literatures regarding elements of positive regulation strategies.
319 elementary students (age ranging from 12 to14) were recruited
among three public elementary schools to survey on their use of
positive emotion regulation strategies. Of 319 subjects, 20 invalid
questionnaire s yielded a response rate of 92%. The data collected
wasanalyzed through methods such as item analysis, factor analysis,
and structural equation models. In reference to the results from item
analysis, the formal survey instrument was reduced to 11 items. A
principal axis factor analysis with varimax was performed on
responses, resulting in a 2-factor equation (savoring strategy and
neutralizing strategy), which accounted for 55.5% of the total
variance. Then, the two-factor structure of scale was also identified by
structural equation models. Finally, the reliability coefficients of the
two factors were Cronbach-s α .92 and .74. Gender difference was
only found in savoring strategy. In conclusion, the positive emotion
regulation strategies questionnaire offers a brief, internally consistent,
and valid self-report measure for understanding the emotional
regulation strategies of children that may be useful to researchers and
applied professionals.
Abstract: This paper presents the simulation of fragmentation
warhead using a hydrocode, Autodyn. The goal of this research is to
determine the lethal range of such a warhead. This study investigates
the lethal range of warheads with and without steel balls as
preformed fragments. The results from the FE simulation, i.e. initial
velocities and ejected spray angles of fragments, are further processed
using an analytical approach so as to determine a fragment hit density
and probability of kill of a modelled warhead. In order to simulate a
plenty of preformed fragments inside a warhead, the model requires
expensive computation resources. Therefore, this study attempts to
model the problem in an alternative approach by considering an
equivalent mass of preformed fragments to the mass of warhead
casing. This approach yields approximately 7% and 20% difference
of fragment velocities from the analytical results for one and two
layers of preformed fragments, respectively. The lethal ranges of the
simulated warheads are 42.6 m and 56.5 m for warheads with one and
two layers of preformed fragments, respectively, compared to 13.85
m for a warhead without preformed fragment. These lethal ranges are
based on the requirement of fragment hit density. The lethal ranges
which are based on the probability of kill are 27.5 m, 61 m and 70 m
for warheads with no preformed fragment, one and two layers of
preformed fragments, respectively.
Abstract: White rust, caused by Albugo candida, is the most
destructive foliar diseases of persian cress, Lepidium sativum in Iran.
Application of fungicide is the most common method for the disease
control. However, regarding the problems created by synthetic
pesticides application, environmentally safe methods are needed to
replace chemical pesticides. In this study, the antifungal activity of
plant natural extracts was investigated for their ability to inhibit
zoospore release from sporangia of A. candida. The crude extract of
46 plants was obtained using methanol. The inhibitory effect of the
extracts was examined by mixing the plant extracts with a
zoosporangial suspension of A. candida (1×106 spore/ml) at three
concentrations, 250, 100 and 50 ppm. The experiments were
conducted in a completely randomized design, with three replicates.
The results of the experiment showed that three out of 46 plants
species, including, Rhus coriaria, Anagallis arvensis and Mespilus
germanica were completely inhibit zoospore release from
zoosporangia of Albugo candida at concentration of 50 ppm.