Abstract: This paper presents the development of a Bayesian
belief network classifier for prediction of graft status and survival
period in renal transplantation using the patient profile information
prior to the transplantation. The objective was to explore feasibility
of developing a decision making tool for identifying the most suitable
recipient among the candidate pool members. The dataset was
compiled from the University of Toledo Medical Center Hospital
patients as reported to the United Network Organ Sharing, and had
1228 patient records for the period covering 1987 through 2009. The
Bayes net classifiers were developed using the Weka machine
learning software workbench. Two separate classifiers were induced
from the data set, one to predict the status of the graft as either failed
or living, and a second classifier to predict the graft survival period.
The classifier for graft status prediction performed very well with a
prediction accuracy of 97.8% and true positive values of 0.967 and
0.988 for the living and failed classes, respectively. The second
classifier to predict the graft survival period yielded a prediction
accuracy of 68.2% and a true positive rate of 0.85 for the class
representing those instances with kidneys failing during the first year
following transplantation. Simulation results indicated that it is
feasible to develop a successful Bayesian belief network classifier for
prediction of graft status, but not the graft survival period, using the
information in UNOS database.
Abstract: Bio-demographic diversity which refers to age and gender of members in a team, has been frequently identified to influence team innovation directly. As the theories expanded, biodemographic diversity was suggested to influence team innovation via psychosocial trait and interaction process. This study examines those suggestions, in which psychosocial trait and interaction process were operationalized as 'participation safety climate' and 'team reflexivity' respectively. The role of team reflexivity as a mediator to participation safety climate and team innovation was also assessed. Due to a small number of teams involved in the study, data were analyzed by using a PLS-graph. While the results show only gender is significantly related to the participation safety climate, which in turn influences team reflexivity and team innovation, there is no statistical evidence that team reflexivity mediates the impact of participation safety climate on team innovation.
Abstract: An adaptive Fuzzy Inference Perceptual model has
been proposed for watermarking of digital images. The model
depends on the human visual characteristics of image sub-regions in
the frequency multi-resolution wavelet domain. In the proposed
model, a multi-variable fuzzy based architecture has been designed to
produce a perceptual membership degree for both candidate
embedding sub-regions and strength watermark embedding factor.
Different sizes of benchmark images with different sizes of
watermarks have been applied on the model. Several experimental
attacks have been applied such as JPEG compression, noises and
rotation, to ensure the robustness of the scheme. In addition, the
model has been compared with different watermarking schemes. The
proposed model showed its robustness to attacks and at the same time
achieved a high level of imperceptibility.
Abstract: The selection for plantation of a particular type of
mustard plant depending on its productivity (pod yield) at the stage
of maturity. The growth of mustard plant dependent on some
parameters of that plant, these are shoot length, number of leaves,
number of roots and roots length etc. As the plant is growing, some
leaves may be fall down and some new leaves may come, so it can
not gives the idea to develop the relationship with the seeds weight at
mature stage of that plant. It is not possible to find the number of
roots and root length of mustard plant at growing stage that will be
harmful of this plant as roots goes deeper to deeper inside the land.
Only the value of shoot length which increases in course of time can
be measured at different time instances. Weather parameters are
maximum and minimum humidity, rain fall, maximum and minimum
temperature may effect the growth of the plant. The parameters of
pollution, water, soil, distance and crop management may be
dominant factors of growth of plant and its productivity. Considering
all parameters, the growth of the plant is very uncertain, fuzzy
environment can be considered for the prediction of shoot length at
maturity of the plant. Fuzzification plays a greater role for
fuzzification of data, which is based on certain membership
functions. Here an effort has been made to fuzzify the original data
based on gaussian function, triangular function, s-function,
Trapezoidal and L –function. After that all fuzzified data are
defuzzified to get normal form. Finally the error analysis
(calculation of forecasting error and average error) indicates the
membership function appropriate for fuzzification of data and use to
predict the shoot length at maturity. The result is also verified using
residual (Absolute Residual, Maximum of Absolute Residual, Mean
Absolute Residual, Mean of Mean Absolute Residual, Median of
Absolute Residual and Standard Deviation) analysis.
Abstract: This paper deals with the application of a fuzzy set in
measuring teachers- beliefs about mathematics. The vagueness of
beliefs was transformed into standard mathematical values using a
fuzzy preferences model. The study employed a fuzzy approach
questionnaire which consists of six attributes for measuring
mathematics teachers- beliefs about mathematics. The fuzzy conjoint
analysis approach based on fuzzy set theory was used to analyze the
data from twenty three mathematics teachers from four secondary
schools in Terengganu, Malaysia. Teachers- beliefs were recorded in
form of degrees of similarity and its levels of agreement. The
attribute 'Drills and practice is one of the best ways of learning
mathematics' scored the highest degree of similarity at 0. 79860 with
level of 'strongly agree'. The results showed that the teachers- beliefs
about mathematics were varied. This is shown by different levels of
agreement and degrees of similarity of the measured attributes.
Abstract: International competitiveness receives much attention
nowadays, but up to now its assessment has been heavily based on
manufacturing industry statistics. This paper addresses the need for
competitiveness indicators that cover the service sector and sets out a
multilevel framework for measuring international services trade
competitiveness. The approach undertaken here aims at
comparatively examining the international competitiveness of the
EU-25 (the twenty-five European Union member states before the 1st
of January 2007), Romanian and Bulgarian services trade, as well as
the last two countries- structure of specialization on the EU-25
services market. The primary changes in the international
competitiveness of three major services sectors – transportation,
travel and other services - are analyzed. This research attempts to
determine the ability of the two recent European Union (EU) member
states to contend with the challenges that might arise from the hard
competition within the enlarged EU, in the field of services trade.
Abstract: The way music is interpreted by the human brain is a very interesting topic, but also an intricate one. Although this domain has been studied for over a century, many gray areas remain in the understanding of music. Recent advances have enabled us to perform accurate measurements of the time taken by the human brain to interpret and assimilate a sound. Cognitive computing provides tools and development environments that facilitate human cognition simulation. ACT-R is a cognitive architecture which offers an environment for implementing human cognitive tasks. This project combines our understanding of the music interpretation by a human listener and the ACT-R cognitive architecture to build SINGER, a computerized simulation for listening and recalling songs. The results are similar to human experimental data. Simulation results also show how it is easier to remember short melodies than long melodies which require more trials to be recalled correctly.
Abstract: A multilayer self organizing neural neural network
(MLSONN) architecture for binary object extraction, guided by a beta
activation function and characterized by backpropagation of errors
estimated from the linear indices of fuzziness of the network output
states, is discussed. Since the MLSONN architecture is designed to
operate in a single point fixed/uniform thresholding scenario, it does
not take into cognizance the heterogeneity of image information in
the extraction process. The performance of the MLSONN architecture
with representative values of the threshold parameters of the beta
activation function employed is also studied. A three layer bidirectional
self organizing neural network (BDSONN) architecture
comprising fully connected neurons, for the extraction of objects from
a noisy background and capable of incorporating the underlying image
context heterogeneity through variable and adaptive thresholding,
is proposed in this article. The input layer of the network architecture
represents the fuzzy membership information of the image scene to
be extracted. The second layer (the intermediate layer) and the final
layer (the output layer) of the network architecture deal with the self
supervised object extraction task by bi-directional propagation of the
network states. Each layer except the output layer is connected to the
next layer following a neighborhood based topology. The output layer
neurons are in turn, connected to the intermediate layer following
similar topology, thus forming a counter-propagating architecture
with the intermediate layer. The novelty of the proposed architecture
is that the assignment/updating of the inter-layer connection weights
are done using the relative fuzzy membership values at the constituent
neurons in the different network layers. Another interesting feature
of the network lies in the fact that the processing capabilities of
the intermediate and the output layer neurons are guided by a beta
activation function, which uses image context sensitive adaptive
thresholding arising out of the fuzzy cardinality estimates of the
different network neighborhood fuzzy subsets, rather than resorting to
fixed and single point thresholding. An application of the proposed
architecture for object extraction is demonstrated using a synthetic
and a real life image. The extraction efficiency of the proposed
network architecture is evaluated by a proposed system transfer index
characteristic of the network.
Abstract: Article 5(3) of the Brussels I Regulation provides that a person domiciled in a Member State may be sued in another Member State in matters relating to tort, delict or quasi-delict, in the courts for the place where the harmful events occurred or may occur. For a number of years Article 5 (3) of the Brussels I Regulation has been at the centre of the debate regarding the intellectual property rights infringement over the Internet. Nothing has been done to adapt the provisions relating to non-internet cases of infringement of intellectual property rights to the context of the Internet. The author’s findings indicate that in the case of intellectual property rights infringement on the Internet, the plaintiff has the option to sue either: the court of the Member State of the event giving rise to the damage: where the publisher of the newspaper is established; the court of the Member State where the damage occurred: where defamatory article is distributed. However, it must be admitted that whilst infringement over the Internet has some similarity to multi-State defamation by means of newspapers, the position is not entirely analogous due to the cross-border nature of the Internet. A simple example which may appropriately illustrate its contentious nature is a defamatory statement published on a website accessible in different Member States, and available in different languages. Therefore, we need to answer the question: how these traditional jurisdictional rules apply in the case of intellectual property rights infringement over the Internet? Should these traditional jurisdictional rules be modified?
Abstract: This paper proposes a new version of the Particle
Swarm Optimization (PSO) namely, Modified PSO (MPSO) for
model order formulation of Single Input Single Output (SISO) linear
time invariant continuous systems. In the General PSO, the
movement of a particle is governed by three behaviors namely
inertia, cognitive and social. The cognitive behavior helps the
particle to remember its previous visited best position. In Modified
PSO technique split the cognitive behavior into two sections like
previous visited best position and also previous visited worst
position. This modification helps the particle to search the target very
effectively. MPSO approach is proposed to formulate the higher
order model. The method based on the minimization of error
between the transient responses of original higher order model and
the reduced order model pertaining to the unit step input. The results
obtained are compared with the earlier techniques utilized, to validate
its ease of computation. The proposed method is illustrated through
numerical example from literature.
Abstract: This paper presents the Literature Review of carbon fiber reinforced polymer (CFRP) strips to reinforced concrete (RC) as a strengthening solution for T-beams. Although a great deal of research has been carried out on Rectangular beams strengthened with Fibre-Reinforced Polymer composites (FRP), Fiber reinforced polymer (FRP) composites have been increasingly studied for their application in the flexural or shear strengthening of reinforced concrete (RC) members. A detailed discussion of the shearstrengthening repair with FRP is undertaken. This paper will be limited to research of CFRP material externally bonded to the tensile face of concrete beams. In particular, research studying the effect of externally applied CFRP materials on the shear performance of reinforced concrete beams will be reported.
Abstract: New Zealand-s product markets experienced a surge in
import competition beginning from the late 1970-s when its
government began to promote a policy of more open markets. This
study considers how the trade liberalization aspect of the policy may
have influenced unionization and union-organizing success. For
describing the trade liberalization, a model shows how the removal of
import tariffs can lead to countervailing influences upon the union
membership of a domestic firm. The evidence supports the prediction
that union membership has been decreased rather than increased. In
the context of debates concerning globalization, it can be said that the
power of unions has been diminished.
Abstract: The aim for this research is to deliberately discuss
how and why the contexts of culture are the main significant factors
which need to be considered when conducting the international
business oversea. As a consequence of understanding these various
factors, the researcher would be able to infer some suggestions to the
international organizations. With this in mind, the results of the
understanding in a national culture environment can support the
organizations to settle its international strategies which may be useful
to develop the national export and import effectiveness. This data
collecting methods will be concentrated upon 5-10 interviews from
the senior members and business officers in the international
company in Thailand by e-mail interview and analyses the individual
manager’s viewpoint. As well as, focus on the questionnaires which
the respondents were selected randomly around 100 samples from
UK and Thailand, together with providing a functional sample size
and comparable to data. The results of the study question the role of
national culture, which contributed to in international business
effectiveness and emphasize the positive and negative aspects, as
well as suggestions to business investors are informed.
Abstract: Imitation learning is considered to be an effective way of teaching humanoid robots and action recognition is the key step to imitation learning. In this paper an online algorithm to recognize
parametric actions with object context is presented. Objects are key instruments in understanding an action when there is uncertainty.
Ambiguities arising in similar actions can be resolved with objectn context. We classify actions according to the changes they make to
the object space. Actions that produce the same state change in the object movement space are classified to belong to the same class. This allow us to define several classes of actions where members of
each class are connected with a semantic interpretation.
Abstract: There is limited evidence from various countries
about the possible impact of various criteria to be used to determine
the scope of the IFRS for SMEs issued in 2009 and, research is
needed in this area. We provide evidence from Romania, an
emerging economy member of the European Union. The aim of this
paper is to analyze in a local setting if size is a relevant factor for
deciding between local and global standards for SMEs. Our results
indicate that size is a moderate indicator of the existence of possible
users interested in financial statements and that there is a difference
between the scopes of the standard determined on various criteria..
Also, we suggest that the international exposure is quite reduced in
the case of SMEs, but is sufficient to suggest that at least some SMEs
would benefit from international comparability of financial
statements
Abstract: The study aims to investigate the impact on board and
audit committee characteristics and firm performance before and
after the revision of MCCG (2007) on GLCs over the period 2005-2010. We used Return on Assets (ROA) as a proxy for firm performance. The data consists of two groups; data collected before
and after the amendments of MCCG (2007). Findings show that
boards of directors with accounting / finance qualifications (BEXP)
are statistically significant with performance for period before the amendments. As for audit committee members with accounting or
finance qualifications (ACEXP), correlation results indicate a
negative association and non-significant results for the years before
amendments. However, the years after the amendments show
positive relationship with highly significant correlations (1%) to ROA. This indicates that the amendments of MCCG 2007 on the
audit committee members- literacy in accounting have impacted the governance structures and performance of GLCs.
Abstract: Data clustering is an important data exploration
technique with many applications in data mining. The k-means
algorithm is well known for its efficiency in clustering large data
sets. However, this algorithm is suitable for spherical shaped clusters
of similar sizes and densities. The quality of the resulting clusters
decreases when the data set contains spherical shaped with large
variance in sizes. In this paper, we introduce a competent procedure
to overcome this problem. The proposed method is based on shifting
the center of the large cluster toward the small cluster, and recomputing
the membership of small cluster points, the experimental
results reveal that the proposed algorithm produces satisfactory
results.
Abstract: The study examined the influence of pay differentials on employee retention in the State Colleges of Education in the South-South Region of Nigeria. 275 subjects drawn from members of the wage negotiating teams in the Colleges were administered questionnaires constructed for study. Analysis of Variance revealed that the observed pay differentials significantly influenced retainership, f(5,269 = 6.223, P< 0.05). However, the Multiple Classification Analysis and Post-Hoc test indicated that employees in two of the Colleges with slightly lower and higher pay levels may probably remain with their employers while employees in other Colleges with the least and highest pay levels suggested quitting. Based on these observations, the influence of pay on employee retention seems inconclusive. Generally, employees in the colleges studied are dissatisfied with current pay levels. Management should confront these challenges by improving pay packages to encourage employees to remain and be dedicated to duty.
Abstract: In this study, we examined gender differences in: (1) a
flexible remembering task, that asked for episodic memory decisions
at an item-specific versus category-based level, and (2) the retrieval
specificity of autobiographical memory during free recall.
Differences favouring women were found on both measures.
Furthermore, a significant association was observed, across gender
groups, between level of specificity in the autobiographical memory
interview and sensitivity to gist on the flexible remembering task.
These results suggest that similar cognitive processes may partially
contribute to both the ability for specific autobiographical recall and
the capacity for inhibition of gist-information on the flexible
remembering task.
Abstract: Probability-based identity disclosure risk
measurement may give the same overall risk for different
anonymization strategy of the same dataset. Some entities in the
anonymous dataset may have higher identification risks than the
others. Individuals are more concerned about higher risks than the
average and are more interested to know if they have a possibility of
being under higher risk. A notation of overall risk in the above
measurement method doesn-t indicate whether some of the involved
entities have higher identity disclosure risk than the others. In this
paper, we have introduced an identity disclosure risk measurement
method that not only implies overall risk, but also indicates whether
some of the members have higher risk than the others. The proposed
method quantifies the overall risk based on the individual risk values,
the percentage of the records that have a risk value higher than the
average and how larger the higher risk values are compared to the
average. We have analyzed the disclosure risks for different
disclosure control techniques applied to original microdata and
present the results.