Abstract: The complexity of today-s software systems makes
collaborative development necessary to accomplish tasks.
Frameworks are necessary to allow developers perform their tasks
independently yet collaboratively. Similarity detection is one of the
major issues to consider when developing such frameworks. It allows
developers to mine existing repositories when developing their own
views of a software artifact, and it is necessary for identifying the
correspondences between the views to allow merging them and
checking their consistency. Due to the importance of the
requirements specification stage in software development, this paper
proposes a framework for collaborative development of Object-
Oriented formal specifications along with a similarity detection
approach to support the creation, merging and consistency checking
of specifications. The paper also explores the impact of using
additional concepts on improving the matching results. Finally, the
proposed approach is empirically evaluated.
Abstract: Soccer simulation is an effort to motivate researchers and practitioners to do artificial and robotic intelligence research; and at the same time put into practice and test the results. Many researchers and practitioners throughout the world are continuously working to polish their ideas and improve their implemented systems. At the same time, new groups are forming and they bring bright new thoughts to the field. The research includes designing and executing robotic soccer simulation algorithms. In our research, a soccer simulation player is considered to be an intelligent agent that is capable of receiving information from the environment, analyze it and to choose the best action from a set of possible ones, for its next move. We concentrate on developing a two-phase method for the soccer player agent to choose its best next move. The method is then implemented into our software system called Nexus simulation team of Ferdowsi University. This system is based on TsinghuAeolus[1] team that was the champion of the world RoboCup soccer simulation contest in 2001 and 2002.
Abstract: One of the main concerns in the Information Technology field is adoption with new technologies in organizations which may result in increasing the usage paste of these technologies.This study aims to look at the issue of culture-s role in accepting and using new technologies in organizations. The study examines the effect of culture on accepting and intention to use new technology in organizations. Studies show culture is one of the most important barriers in adoption new technologies. The model used for accepting and using new technology is Technology Acceptance Model (TAM), while for culture and dimensions a well-known theory by Hofsted was used. Results of the study show significant effect of culture on intention to use new technologies. All four dimensions of culture were tested to find the strength of relationship with behavioral intention to use new technologies. Findings indicate the important role of culture in the level of intention to use new technologies and different role of each dimension to improve adaptation process. The study suggests that transferring of new technologies efforts are most likely to be successful if the parties are culturally aligned.
Abstract: Business process management (BPM) has become
widely accepted within business community as a means for
improving business performance. However, it is of the highest
importance to incorporate BPM as part of the curriculum at the
university level education in order to achieve the appropriate
acceptance of the method. Goal of the paper is to determine the
current state of education in business process management (BPM) at
the Croatian universities and abroad. It investigates the applied forms
of instruction and teaching methods and gives several proposals for
BPM courses improvement. Since majority of undergraduate and
postgraduate students have limited understanding of business
processes and lack of any practical experience, there is a need for
introducing new teaching approaches. Therefore, we offer some
suggestions for further improvement, among which the introduction
of simulation games environment in BPM education is strongly
recommended.
Abstract: Toughening of polyamide 6 (PA6)/ Nanoclay (NC) nanocomposites with styrene-ethylene/butadiene-styrene copolymer (SEBS) using maleated styrene-ethylene/butadiene-styrene copolymer (mSEBS)/ as a compatibilizer were investigated by blending them in a co-rotating twin-screw extruder. Response surface method of experimental design was used for optimizing the material and processing parameters. Effect of four factors, including SEBS, mSEBS and NC contents as material variables and order of mixing as a processing factor, on toughness of hybrid nanocomposites were studied. All the prepared samples showed ductile behavior and low temperature Izod impact toughness of some of the hybrid nanocomposites demonstrated 900% improvement compared to the PA6 matrix while the modulus showed maximum enhancement of 20% compared to the pristine PA6 resin.
Abstract: One major source of performance decline in speaker
recognition system is channel mismatch between training and testing.
This paper focuses on improving channel robustness of speaker
recognition system in two aspects of channel compensation technique
and channel robust features. The system is text-independent speaker
identification system based on two-stage recognition. In the aspect of
channel compensation technique, this paper applies MAP (Maximum
A Posterior Probability) channel compensation technique, which was
used in speech recognition, to speaker recognition system. In the
aspect of channel robust features, this paper introduces
pitch-dependent features and pitch-dependent speaker model for the
second stage recognition. Based on the first stage recognition to
testing speech using GMM (Gaussian Mixture Model), the system
uses GMM scores to decide if it needs to be recognized again. If it
needs to, the system selects a few speakers from all of the speakers
who participate in the first stage recognition for the second stage
recognition. For each selected speaker, the system obtains 3
pitch-dependent results from his pitch-dependent speaker model, and
then uses ANN (Artificial Neural Network) to unite the 3
pitch-dependent results and 1 GMM score for getting a fused result.
The system makes the second stage recognition based on these fused
results. The experiments show that the correct rate of two-stage
recognition system based on MAP channel compensation technique
and pitch-dependent features is 41.7% better than the baseline system
for closed-set test.
Abstract: Subjective loneliness describes people who feel a
disagreeable or unacceptable lack of meaningful social relationships,
both at the quantitative and qualitative level. The studies to be
presented tested an Italian 18-items self-report loneliness measure,
that included items adapted from scales previously developed,
namely a short version of the UCLA (Russell, Peplau and Cutrona,
1980), and the 11-items Loneliness scale by De Jong-Gierveld &
Kamphuis (JGLS; 1985). The studies aimed at testing the developed
scale and at verifying whether loneliness is better conceptualized as a
unidimensional (so-called 'general loneliness') or a bidimensional
construct, namely comprising the distinct facets of social and
emotional loneliness. The loneliness questionnaire included 2 singleitem
criterion measures of sad mood, and social contact, and asked
participants to supply information on a number of socio-demographic
variables. Factorial analyses of responses obtained in two
preliminary studies, with 59 and 143 Italian participants respectively,
showed good factor loadings and subscale reliability and confirmed
that perceived loneliness has clearly two components, a social and an
emotional one, the latter measured by two subscales, a 7-item
'general' loneliness subscale derived from UCLA, and a 6–item
'emotional' scale included in the JGLS. Results further showed that
type and amount of loneliness are related, negatively, to frequency of
social contacts, and, positively, to sad mood. In a third study data
were obtained from a nation-wide sample of 9.097 Italian subjects,
12 to about 70 year-olds, who filled the test on-line, on the Italian
web site of a large-audience magazine, Focus. The results again
confirmed the reliability of the component subscales, namely social,
emotional, and 'general' loneliness, and showed that they were
highly correlated with each other, especially the latter two.
Loneliness scores were significantly predicted by sex, age, education
level, sad mood and social contact, and, less so, by other variables –
e.g., geographical area and profession. The scale validity was
confirmed by the results of a fourth study, with elderly men and
women (N 105) living at home or in residential care units. The three
subscales were significantly related, among others, to depression, and
to various measures of the extension of, and satisfaction with, social
contacts with relatives and friends. Finally, a fifth study with 315
career-starters showed that social and emotional loneliness correlate
with life satisfaction, and with measures of emotional intelligence.
Altogether the results showed a good validity and reliability in the
tested samples of the entire scale, and of its components.
Abstract: The purpose of planned islanding is to construct a
power island during system disturbances which are commonly
formed for maintenance purpose. However, in most of the cases
island mode operation is not allowed. Therefore distributed
generators (DGs) must sense the unplanned disconnection from the
main grid. Passive technique is the most commonly used method for
this purpose. However, it needs improvement in order to identify the
islanding condition. In this paper an effective method for
identification of islanding condition based on phase space and neural
network techniques has been developed. The captured voltage
waveforms at the coupling points of DGs are processed to extract the
required features. For this purposed a method known as the phase
space techniques is used. Based on extracted features, two neural
network configuration namely radial basis function and probabilistic
neural networks are trained to recognize the waveform class.
According to the test result, the investigated technique can provide
satisfactory identification of the islanding condition in the
distribution system.
Abstract: From an economic standpoint the current and future
road traffic situation in urban areas is a cost factor. Traffic jams and
congestion prolong journey times and tie up resources in trucks and
personnel. Many discussions about imposing charges or tolls for
cities in Europe in order to reduce traffic congestion are currently in
progress. Both of these effects lead – directly or indirectly - to
additional costs for the urban distribution systems in retail
companies. One approach towards improving the efficiency of retail
distribution systems, and thus towards avoiding negative
environmental factors in urban areas, is horizontal collaboration for
deliveries to retail outlets – Urban Retail Logistics. This paper
presents a classification system to help reveal where cooperation
between retail companies is possible and makes sense for deliveries
to retail outlets in urban areas.
Abstract: Nowadays, the plant location selection has a critical
impact on the performance of numerous companies. In this paper, a
methodology is presented to solve this problem. The three decision
making methods, namely Delphi, AHP and improved VIKOR, are
hybridized in order to make the best use of information available
based on the decision makers or experts. In this respect, the aim of
using Delphi is to select the most influential criteria by a few decision
makers. The AHP is utilized to give weights of the selected criteria.
Finally, the improved VIKOR method is applied to rank alternatives.
At the end of paper, an application example demonstrates the
applicability of the proposed methodology.
Abstract: This paper presents a new classification algorithm using colour and texture for obstacle detection. Colour information is computationally cheap to learn and process. However in many cases, colour alone does not provide enough information for classification. Texture information can improve classification performance but usually comes at an expensive cost. Our algorithm uses both colour and texture features but texture is only needed when colour is unreliable. During the training stage, texture features are learned specifically to improve the performance of a colour classifier. The algorithm learns a set of simple texture features and only the most effective features are used in the classification stage. Therefore our algorithm has a very good classification rate while is still fast enough to run on a limited computer platform. The proposed algorithm was tested with a challenging outdoor image set. Test result shows the algorithm achieves a much better trade-off between classification performance and efficiency than a typical colour classifier.
Abstract: Mobile Ad hoc network consists of a set of mobile
nodes. It is a dynamic network which does not have fixed topology.
This network does not have any infrastructure or central
administration, hence it is called infrastructure-less network. The
change in topology makes the route from source to destination as
dynamic fixed and changes with respect to time. The nature of
network requires the algorithm to perform route discovery, maintain
route and detect failure along the path between two nodes [1]. This
paper presents the enhancements of ARA [2] to improve the
performance of routing algorithm. ARA [2] finds route between
nodes in mobile ad-hoc network. The algorithm is on-demand source
initiated routing algorithm. This is based on the principles of swarm
intelligence. The algorithm is adaptive, scalable and favors load
balancing. The improvements suggested in this paper are handling of
loss ants and resource reservation.
Abstract: In this paper, backup and recovery technique for Peer
to Peer applications, such as a distributed asynchronous Web-Based
Training system that we have previously proposed. In order to
improve the scalability and robustness of this system, all contents and
function are realized on mobile agents. These agents are distributed
to computers, and they can obtain using a Peer to Peer network
that modified Content-Addressable Network. In the proposed system,
although entire services do not become impossible even if some
computers break down, the problem that contents disappear occurs
with an agent-s disappearance. As a solution for this issue, backups
of agents are distributed to computers. If a failure of a computer is
detected, other computers will continue service using backups of the
agents belonged to the computer.
Abstract: In Iran, due to abundance of energy resources, energy consumption is extraordinarily higher than international standards and transportation sector is considered to be one of the major consumers of energy. Moreover, air pollution in urban areas as a result of high dependence on private vehicle and lower standards of vehicles, high subsidies spent on fuel and time waste due to traffic congestion in urban areas all have led to speculations on new strategies and policies in order to control energy consumption in transportation sector. These strategies and policies will be introduced in this paper and their consequences will be analyzed with consideration to socio-economic factors affecting the urban society of Iran. Besides, the intention is to suggest and analyze new approaches such as broader application of public transportation system, demand management in transport sector, replacement of deteriorated vehicles, quality improvement in car manufacture and introduction of substitute fuels.
Abstract: This paper proposes a synchronized random switching frequency pulse width modulation (SRSFPWM). In this technique, the clock signal is used to control the random noise frequency which is produced by the feedback voltage of a hysteresis circuit. These make the triangular carrier frequency equaling to the random noise frequency in each switching period with the symmetrical positive and negative slopes of triangular carrier. Therefore, there is no error voltage in PWM signal. The PSpice simulated results shown the proposed technique improved the performance in case of low frequency harmonics of PWM signal comparing with conventional random switching frequency PWM.
Abstract: This paper presents the determination of the proper
quality costs parameters which provide the optimum return. The
system dynamics simulation was applied. The simulation model was
constructed by the real data from a case of the electronic devices
manufacturer in Thailand. The Steepest Descent algorithm was
employed to optimise. The experimental results show that the
company should spend on prevention and appraisal activities for 850
and 10 Baht/day respectively. It provides minimum cumulative total
quality cost, which is 258,000 Baht in twelve months. The effect of
the step size in the stage of improving the variables to the optimum
was also investigated. It can be stated that the smaller step size
provided a better result with more experimental runs. However, the
different yield in this case is not significant in practice. Therefore, the
greater step size is recommended because the region of optima could
be reached more easily and rapidly.
Abstract: Diabetes is one of the high prevalence diseases
worldwide with increased number of complications, with retinopathy
as one of the most common one. This paper describes how data
mining and case-based reasoning were integrated to predict
retinopathy prevalence among diabetes patients in Malaysia. The
knowledge base required was built after literature reviews and
interviews with medical experts. A total of 140 diabetes patients- data
were used to train the prediction system. A voting mechanism selects
the best prediction results from the two techniques used. It has been
successfully proven that both data mining and case-based reasoning
can be used for retinopathy prediction with an improved accuracy of
85%.
Abstract: There are multiple reasons to expect that detecting the
word order errors in a text will be a difficult problem, and detection
rates reported in the literature are in fact low. Although grammatical
rules constructed by computer linguists improve the performance of
grammar checker in word order diagnosis, the repairing task is still
very difficult. This paper presents an approach for repairing word
order errors in English text by reordering words in a sentence and
choosing the version that maximizes the number of trigram hits
according to a language model. The novelty of this method concerns
the use of an efficient confusion matrix technique for reordering the
words. The comparative advantage of this method is that works with
a large set of words, and avoids the laborious and costly process of
collecting word order errors for creating error patterns.
Abstract: This work deals with the initial applications and formulation of an anisotropic plastic-damage constitutive model proposed for non-linear analysis of reinforced concrete structures submitted to a loading with change of the sign. The original constitutive model is based on the fundamental hypothesis of energy equivalence between real and continuous medium following the concepts of the Continuum Damage Mechanics. The concrete is assumed as an initial elastic isotropic medium presenting anisotropy, permanent strains and bimodularity (distinct elastic responses whether traction or compression stress states prevail) induced by damage evolution. In order to take into account the bimodularity, two damage tensors governing the rigidity in tension or compression regimes are introduced. Then, some conditions are introduced in the original version of the model in order to simulate the damage unilateral effect. The three-dimensional version of the proposed model is analyzed in order to validate its formulation when compared to micromechanical theory. The one-dimensional version of the model is applied in the analyses of a reinforced concrete beam submitted to a loading with change of the sign. Despite the parametric identification problems, the initial applications show the good performance of the model.
Abstract: Emotion in speech is an issue that has been attracting
the interest of the speech community for many years, both in the
context of speech synthesis as well as in automatic speech
recognition (ASR). In spite of the remarkable recent progress in
Large Vocabulary Recognition (LVR), it is still far behind the
ultimate goal of recognising free conversational speech uttered by
any speaker in any environment. Current experimental tests prove
that using state of the art large vocabulary recognition systems the
error rate increases substantially when applied to
spontaneous/emotional speech. This paper shows that recognition
rate for emotionally coloured speech can be improved by using a
language model based on increased representation of emotional
utterances.