Abstract: In this longitudinal study, we examined the moderating role of personality in the relationship between communication behaviors and long-term dyadic adjustment. A sample of 82 couples completed the NEO Five-Factor Inventory and the Dyadic Adjustment Scale. These couples were also videotaped during a 15-minute problem-solving discussion. Approximately 2.5 years later, these couples completed again the Dyadic Adjustment Scale. Results show that personality of both men and women moderates the relationship between communication behaviors of the partner and long-term dyadic adjustment of the individual. Women-s openness and men-s extraversion moderate the relationship between some communication behaviors and long-term dyadic adjustment
Abstract: Time series forecasting is an important and widely
popular topic in the research of system modeling. This paper
describes how to use the hybrid PSO-RLSE neuro-fuzzy learning
approach to the problem of time series forecasting. The PSO
algorithm is used to update the premise parameters of the
proposed prediction system, and the RLSE is used to update the
consequence parameters. Thanks to the hybrid learning (HL)
approach for the neuro-fuzzy system, the prediction performance
is excellent and the speed of learning convergence is much faster
than other compared approaches. In the experiments, we use the
well-known Mackey-Glass chaos time series. According to the
experimental results, the prediction performance and accuracy in
time series forecasting by the proposed approach is much better
than other compared approaches, as shown in Table IV. Excellent
prediction performance by the proposed approach has been
observed.
Abstract: Internet is without any doubt the fastest and effective mean of communication making it possible to reach a great number of people in the world. It draws its base from exchange points. Indeed exchange points are used to inter-connect various Internet suppliers and operators in order to allow them to exchange traffic and it is with these interconnections that Internet made its great strides. They thus make it possible to limit the traffic delivered via the operators of transits. This limitation allows a significant improvement of the quality of service, a reduction in the latency time just as a reduction of the cost of connection for the final subscriber. Through this article we will show how the installation of an IXP allows an improvement and a diversification of the services just as a reduction of the Internet connection costs.
Abstract: This paper presents the methodology from machine
learning approaches for short-term rain forecasting system. Decision
Tree, Artificial Neural Network (ANN), and Support Vector Machine
(SVM) were applied to develop classification and prediction models
for rainfall forecasts. The goals of this presentation are to
demonstrate (1) how feature selection can be used to identify the
relationships between rainfall occurrences and other weather
conditions and (2) what models can be developed and deployed for
predicting the accurate rainfall estimates to support the decisions to
launch the cloud seeding operations in the northeastern part of
Thailand. Datasets collected during 2004-2006 from the
Chalermprakiat Royal Rain Making Research Center at Hua Hin,
Prachuap Khiri khan, the Chalermprakiat Royal Rain Making
Research Center at Pimai, Nakhon Ratchasima and Thai
Meteorological Department (TMD). A total of 179 records with 57
features was merged and matched by unique date. There are three
main parts in this work. Firstly, a decision tree induction algorithm
(C4.5) was used to classify the rain status into either rain or no-rain.
The overall accuracy of classification tree achieves 94.41% with the
five-fold cross validation. The C4.5 algorithm was also used to
classify the rain amount into three classes as no-rain (0-0.1 mm.),
few-rain (0.1- 10 mm.), and moderate-rain (>10 mm.) and the overall
accuracy of classification tree achieves 62.57%. Secondly, an ANN
was applied to predict the rainfall amount and the root mean square
error (RMSE) were used to measure the training and testing errors of
the ANN. It is found that the ANN yields a lower RMSE at 0.171 for
daily rainfall estimates, when compared to next-day and next-2-day
estimation. Thirdly, the ANN and SVM techniques were also used to
classify the rain amount into three classes as no-rain, few-rain, and
moderate-rain as above. The results achieved in 68.15% and 69.10%
of overall accuracy of same-day prediction for the ANN and SVM
models, respectively. The obtained results illustrated the comparison
of the predictive power of different methods for rainfall estimation.
Abstract: The paper represents a reflection on how to select proper indicators to assess the progress of regional contexts towards a knowledge-based society. Taking the first research methodologies elaborated at an international level (World Bank, OECD, etc.) as a reference point, this work intends to identify a set of indicators of the knowledge economy suitable to adequately understand in which manner and to which extent the territorial development dynamics are correlated with the knowledge-base of the considered local society. After a critical survey of the variables utilized within other approaches adopted by international or national organizations, this paper seeks to elaborate a framework of variables, named Regional Knowledge Economy Indicators (ReKEI), necessary to describe the knowledge-based relations of subnational socio-economic contexts. The realization of this framework has a double purpose: an analytical one consisting in highlighting the regional differences in the governance of knowledge based processes, and an operative one consisting in providing some reference parameters for contributing to increasing the effectiveness of those economic policies aiming at enlarging the knowledge bases of local societies.
Abstract: The main objective of this study was to remove and recover Ni, Cu and Fe from a mixed metal system using sodium hypophosphite as a reducing agent and nickel powder as seeding material. The metal systems studied consisted of Ni-Cu, Ni-Fe and Ni-Cu-Fe solutions. A 5 L batch reactor was used to conduct experiments where 100 mg/l of each respective metal was used. It was found that the metals were reduced to their elemental form with removal efficiencies of over 80%. The removal efficiency decreased in the order Fe>Ni>Cu. The metal powder obtained contained between 97-99% Ni and was almost spherical and porous. Size enlargement by aggregation was the dominant particulate process.
Abstract: Cardiovascular diseases, principally atherosclerosis, are responsible for 30% of world deaths. Atherosclerosis is due to the formation of plaque. The fatty plaque may be at risk of rupture, leading typically to stroke and heart attack. The plaque is usually associated with a high degree of lumen reduction, called a stenosis.It is increasingly recognized that the initiation and progression of disease and the occurrence of clinical events is a complex interplay between the local biomechanical environment and the local vascular biology. The aim of this study is to investigate the flow behavior through a stenosed artery. A physical experiment was performed using an artery model and blood analogue fluid. An axisymmetric model constructed consists of contraction and expansion region that follow a mathematical form of cosine function. A 30% diameter reduction was used in this study. The flow field was measured using particle image velocimetry (PIV). Spherical particles with 20μm diameter were seeded in a water-glycerol-NaCl mixture. Steady flow Reynolds numbers are 250. The area of interest is the region after the stenosis where the flow separation occurs. The velocity field was measured and the velocity gradient was investigated. There was high particle concentration in the recirculation zone. High velocity gradient formed immediately after the stenosis throat created a lift force that enhanced particle migration to the flow separation area.
Abstract: Static analysis of source code is used for auditing web
applications to detect the vulnerabilities. In this paper, we propose a
new algorithm to analyze the PHP source code for detecting LFI and
RFI potential vulnerabilities. In our approach, we first define some
patterns for finding some functions which have potential to be abused
because of unhandled user inputs. More precisely, we use regular
expression as a fast and simple method to define some patterns for
detection of vulnerabilities. As inclusion functions could be also used
in a safe way, there could occur many false positives (FP). The first
cause of these FP-s could be that the function does not use a usersupplied
variable as an argument. So, we extract a list of usersupplied
variables to be used for detecting vulnerable lines of code.
On the other side, as vulnerability could spread among the variables
like by multi-level assignment, we also try to extract the hidden usersupplied
variables. We use the resulted list to decrease the false
positives of our method. Finally, as there exist some ways to prevent
the vulnerability of inclusion functions, we define also some patterns
to detect them and decrease our false positives.
Abstract: This paper investigates the effect of product substitution in the single-period 'newsboy-type' problem in a fuzzy environment. It is supposed that the single-period problem operates under uncertainty in customer demand, which is described by imprecise terms and modelled by fuzzy sets. To perform this analysis, we consider the fuzzy model for two-item with upward substitution. This upward substitutability is reasonable when the products can be stored according to certain attribute levels such as quality, brand or package size. We show that the explicit consideration of this substitution opportunity increase the average expected profit. Computational study is performed to observe the benefits of product's substitution.
Abstract: A preliminary evaluation of the urban land system is
presented in the article together with the instruments of land policy in
Serbia. The main reason for the analysis is demand for
definition of reform framework for urban land management in
Serbia in the period of transition towards market-led system. It
is concluded that due to the limitations of the current regulation it
will be impossible in the future to apply market principles in the
urban land policy (supply and demand of land, land capitalization,
investment efficiency, et al.). Based on the estimation that the urban
land system and land policy are key factors of competitiveness
between regions and towns in Serbia, it is necessary to initiate
changes in this field. There are indicated on an option of privatization
of urban public land and possible establishment of leasehold land. A
comparative analysis of the possibilities of the reform urban land
system in Serbia has been carried out in relation to two approaches of
market systems: (a) with dominant private ownership of urban land
(neo/liberal approach) and (b) with dominant public ownership of
urban land (system of leasehold)whose findings can be a basis for
further study of the new system in Serbia.. The attanied results are
part of studies matter for the making of Strategy of territorial
development of Serbia.
Abstract: Although lots of research work has been done for
human pose recognition, the view-point of cameras is still critical
problem of overall recognition system. In this paper, view-point
insensitive human pose recognition is proposed. The aims of the
proposed system are view-point insensitivity and real-time processing.
Recognition system consists of feature extraction module, neural
network and real-time feed forward calculation. First, histogram-based
method is used to extract feature from silhouette image and it is
suitable for represent the shape of human pose. To reduce the
dimension of feature vector, Principle Component Analysis(PCA) is
used. Second, real-time processing is implemented by using Compute
Unified Device Architecture(CUDA) and this architecture improves
the speed of feed-forward calculation of neural network. We
demonstrate the effectiveness of our approach with experiments on
real environment.
Abstract: Increasing demand on the performance of Subsea
Production Systems (SPS) suggests a need for more detailed
investigation of fluid behavior taking place in subsea equipment.
Complete CFD cool down analyses of subsea equipment are very
time demanding. The objective of this paper is to investigate a
Locked CFD approach, which enables significant reduction of the
computational time and at the same time maintains sufficient
accuracy during thermal cool down simulations. The result
comparison of a dead leg simulation using the Full CFD and the three
LCFD-methods confirms the validity of the locked flow field
assumption for the selected case. For the tested case the LCFD
simulation speed up by factor of 200 results in the absolute thermal
error of 0.5 °C (3% relative error), speed up by factor of 10 keeps the
LCFD results within 0.1 °C (0.5 % relative error) comparing to the
Full CFD.
Abstract: In this paper, we proposed the distribution of mesh
normal vector direction as a feature descriptor of a 3D model. A
normal vector shows the entire shape of a model well. The
distribution of normal vectors was sampled in proportion to each
polygon's area so that the information on the surface with less surface
area may be less reflected on composing a feature descriptor in order
to enhance retrieval performance. At the analysis result of ANMRR,
the enhancement of approx. 12.4%~34.7% compared to the existing
method has also been indicated.
Abstract: In this paper, a new approach for quality assessment
tasks in lossy compressed digital video is proposed. The research
activity is based on the visual fixation data recorded by an eye
tracker. The method involved both a new paradigm for subjective
quality evaluation and the subsequent statistical analysis to match
subjective scores provided by the observer to the data obtained from
the eye tracker experiments. The study brings improvements to the
state of the art, as it solves some problems highlighted in literature.
The experiments prove that data obtained from an eye tracker can be
used to classify videos according to the level of impairment due to
compression. The paper presents the methodology, the experimental
results and their interpretation. Conclusions suggest that the eye
tracker can be useful in quality assessment, if data are collected and
analyzed in a proper way.
Abstract: A group of Stellite alloys are studied in consideration
of temperature effects on their hardness and wear resistance. The
hardness test is conducted on a micro-hardness tester with a hot stage
equipped that allows heating the specimen up to 650°C. The wear
resistance of each alloy is evaluated using a pin-on-disc tribometer
with a heating furnace built-in that provides the temperature capacity
up to 450°C. The experimental results demonstrate that the hardness
and wear resistance of Stellite alloys behave differently at room
temperature and at high temperatures. The wear resistance of Stellite
alloys at room temperature mainly depends on their carbon content and
also influenced by the tungsten content in the alloys. However, at high
temperatures the wear mechanisms of Stellite alloys become more
complex, involving multiple factors. The relationships between
chemical composition, microstructure, hardness and wear resistance of
these alloys are studied, with focus on temperature effect on these
relations.
Abstract: Tool wear and surface roughness prediction plays a
significant role in machining industry for proper planning and control
of machining parameters and optimization of cutting conditions. This
paper deals with developing an artificial neural network (ANN)
model as a function of cutting parameters in turning steel under
minimum quantity lubrication (MQL). A feed-forward
backpropagation network with twenty five hidden neurons has been
selected as the optimum network. The co-efficient of determination
(R2) between model predictions and experimental values are 0.9915,
0.9906, 0.9761 and 0.9627 in terms of VB, VM, VS and Ra
respectively. The results imply that the model can be used easily to
forecast tool wear and surface roughness in response to cutting
parameters.
Abstract: The focus of this paper is to highlight the design and
development of an educational game prototype as an evaluation
instrument for the Malaysia driving license static test. This
educational game brings gaming technology into the conventional
objective static test to make it more effective, real and interesting.
From the feeling of realistic, the future driver can learn something,
memorized and use it in the real life. The current online objective
static test only make the user memorized the answer without knowing
and understand the true purpose of the question. Therefore, in real
life, they will not behave as expected due to behavior and moral
lacking. This prototype has been developed inform of multiple-choice
questions integrated with 3D gaming environment to make it simulate
the real environment and scenarios. Based on the testing conducted,
the respondent agrees with the use of this game prototype it can
increase understanding and promote obligation towards traffic rules.
Abstract: The commercial finite element program LS-DYNA was employed to evaluate the response and energy absorbing capacity of cylindrical metal tubes that are externally wrapped with composite. The effects of composite wall thickness, loading conditions and fiber ply orientation were examined. The results demonstrate that a wrapped composite can be utilized effectively to enhance the crushing characteristics and energy absorbing capacity of the tubes. Increasing the thickness of the composite increases the mean force and the specific energy absorption under both static and dynamic crushing. The ply pattern affects the energy absorption capacity and the failure mode of the metal tube and the composite material property is also significant in determining energy absorption efficiency.
Abstract: Renewable and non-renewable resource constraints have been vast studied in theoretical fields of project scheduling problems. However, although cumulative resources are widespread in practical cases, the literature on project scheduling problems subject to these resources is scant. So in order to study this type of resources more, in this paper we use the framework of a resource constrained project scheduling problem (RCPSP) with finish-start precedence relations between activities and subject to the cumulative resources in addition to the renewable resources. We develop a branch and bound algorithm for this problem customizing precedence tree algorithm of RCPSP. We perform extensive experimental analysis on the algorithm to check its effectiveness and performance for solving different instances of the problem in question.
Abstract: With the development of technology, the growing
trend of fast and safe passenger transport, air pollution, traffic
congestion, increase in problems such as the increasing population
and the high cost of private vehicle usage made many cities around
the world with a population of more or less, start to build rail systems
as a means of urban transport in order to ensure the economic and
environmental sustainability and more efficient use of land in the
city. The implementation phase of rail systems costs much more than
other public transport systems. However, social and economic returns
in the long term made these systems the most popular investment tool
for planned and developing cities.
In our country, the purpose, goals and policies of transportation
plans are away from integrity, and the problems are not clearly
detected. Also, not defined and incomplete assessment of
transportation systems and insufficient financial analysis are the most
important cause of failure. Rail systems and other transportation
systems to be addressed as a whole is seen as the main factor in
increasing efficiency in applications that are not integrated yet in our
country to come to this point has led to the problem.