Abstract: The purpose of this paper is to develop models that would enable predicting student success. These models could improve allocation of students among colleges and optimize the newly introduced model of government subsidies for higher education. For the purpose of collecting data, an anonymous survey was carried out in the last year of undergraduate degree student population using random sampling method. Decision trees were created of which two have been chosen that were most successful in predicting student success based on two criteria: Grade Point Average (GPA) and time that a student needs to finish the undergraduate program (time-to-degree). Decision trees have been shown as a good method of classification student success and they could be even more improved by increasing survey sample and developing specialized decision trees for each type of college. These types of methods have a big potential for use in decision support systems.
Abstract: In today-s information age, numbers of organizations
are still arguing on capitalizing the values of Information Technology
(IT) and Knowledge Management (KM) to which individuals can
benefit from and effective communication among the individuals can
be established. IT exists in enabling positive improvement for
communication among knowledge workers (k-workers) with a
number of social network technology domains at workplace. The
acceptance of digital discourse in sharing of knowledge and
facilitating the knowledge and information flows at most of the
organizations indeed impose the culture of knowledge sharing in
Digital Social Networks (DSN). Therefore, this study examines
whether the k-workers with IT background would confer an effect on
the three knowledge characteristics -- conceptual, contextual, and
operational. Derived from these three knowledge characteristics, five
potential factors will be examined on the effects of knowledge
exchange via e-mail domain as the chosen query. It is expected, that
the results could provide such a parameter in exploring how DSN
contributes in supporting the k-workers- virtues, performance and
qualities as well as revealing the mutual point between IT and KM.
Abstract: Automatic segmentation of skin lesions is the first step
towards the automated analysis of malignant melanoma. Although
numerous segmentation methods have been developed, few studies
have focused on determining the most effective color space for
melanoma application. This paper proposes an automatic segmentation
algorithm based on color space analysis and clustering-based histogram
thresholding, a process which is able to determine the optimal
color channel for detecting the borders in dermoscopy images. The
algorithm is tested on a set of 30 high resolution dermoscopy images.
A comprehensive evaluation of the results is provided, where borders
manually drawn by four dermatologists, are compared to automated
borders detected by the proposed algorithm, applying three previously
used metrics of accuracy, sensitivity, and specificity and a new metric
of similarity. By performing ROC analysis and ranking the metrics,
it is demonstrated that the best results are obtained with the X and
XoYoR color channels, resulting in an accuracy of approximately
97%. The proposed method is also compared with two state-of-theart
skin lesion segmentation methods.
Abstract: The Knowledge Management (KM) Criteria is an
essential foundation to evaluate KM outcomes. Different sets of
criteria were developed and tailored by many researchers to
determine the results of KM initiatives. However, literature review
has emphasized on incomplete set of criteria for evaluating KM
outcomes. Hence, this paper tried to address the problem of
determining the criteria for measuring knowledge management
outcomes among different types of Malaysian organizations.
Successively, this paper was assumed to develop widely accepted
criteria to measure success of knowledge management efforts for
Malaysian organizations. Our analysis approach was based on the
ANOVA procedure to compare a set of criteria among different types
of organizations. This set of criteria was exploited from literature
review. It is hoped that this study provides a better picture for
different types of Malaysian organizations to establish a
comprehensive set of criteria due to measure results of KM programs.
Abstract: To overcome the product overload of Internet
shoppers, we introduce a semantic recommendation procedure which
is more efficient when applied to Internet shopping malls. The
suggested procedure recommends the semantic products to the
customers and is originally based on Web usage mining, product
classification, association rule mining, and frequently purchasing.
We applied the procedure to the data set of MovieLens Company for
performance evaluation, and some experimental results are provided.
The experimental results have shown superior performance in
terms of coverage and precision.
Abstract: Travelling salesman problem (TSP) is a combinational
optimization problem and solution approaches have been applied
many real world problems. Pure TSP assumes the cities to visit are
fixed in time and thus solutions are created to find shortest path
according to these point. But some of the points are canceled to visit
in time. If the problem is not time crucial it is not important to
determine new routing plan but if the points are changing rapidly and
time is necessary do decide a new route plan a new approach should
be applied in such cases. We developed a route plan transfer method
based on transfer learning and we achieved high performance against
determining a new model from scratch in every change.
Abstract: Flood management is one of the important fields in
urban storm water management. Floods are influenced by the
increase of huge storm event, or improper planning of the area. This study mainly provides the flood protection in four stages; planning,
flood event, responses and evaluation. However it is most effective then flood protection is considered in planning/design and
evaluation stages since both stages represent the land development of the area. Structural adjustments are often more reliable than nonstructural
adjustments in providing flood protection, however
structural adjustments are constrained by numerous factors such as
political constraints and cost. Therefore it is important to balance
both adjustments with the situation. The technical decisions provided
will have to be approved by the higher-ups who have the power to
decide on the final solution. Costs however, are the biggest factor in
determining the final decision. Therefore this study recommends
flood protection system should have been integrated and enforces
more in the early stages (planning and design) as part of the storm
water management plan. Factors influencing the technical decisions
provided should be reduced as low as possible to avoid a reduction in
the expected performance of the proposed adjustments.
Abstract: Numerical analysis naturally finds applications in all
fields of engineering and the physical sciences, but in the
21st century, the life sciences and even the arts have adopted
elements of scientific computations. The numerical data analysis
became key process in research and development of all the fields [6].
In this paper we have made an attempt to analyze the specified
numerical patterns with reference to the association rule mining
techniques with minimum confidence and minimum support mining
criteria. The extracted rules and analyzed results are graphically
demonstrated. Association rules are a simple but very useful form of
data mining that describe the probabilistic co-occurrence of certain
events within a database [7]. They were originally designed to
analyze market-basket data, in which the likelihood of items being
purchased together within the same transactions are analyzed.
Abstract: Data mining uses a variety of techniques each of which
is useful for some particular task. It is important to have a deep
understanding of each technique and be able to perform sophisticated
analysis. In this article we describe a tool built to simulate a variation
of the Kohonen network to perform unsupervised clustering and
support the entire data mining process up to results visualization. A
graphical representation helps the user to find out a strategy to
optimize classification by adding, moving or delete a neuron in order
to change the number of classes. The tool is able to automatically
suggest a strategy to optimize the number of classes optimization, but
also support both tree classifications and semi-lattice organizations of
the classes to give to the users the possibility of passing from one
class to the ones with which it has some aspects in common.
Examples of using tree and semi-lattice classifications are given to
illustrate advantages and problems. The tool is applied to classify
macroeconomic data that report the most developed countries- import
and export. It is possible to classify the countries based on their
economic behaviour and use the tool to characterize the commercial
behaviour of a country in a selected class from the analysis of
positive and negative features that contribute to classes formation.
Possible interrelationships between the classes and their meaning are
also discussed.
Abstract: In this paper we report a study aimed at determining
the effects of animation on usability and appeal of educational
software user interfaces. Specifically, the study compares 3
interfaces developed for the Mathsigner™ program: a static
interface, an interface with highlighting/sound feedback, and an
interface that incorporates five Disney animation principles. The
main objectives of the comparative study were to: (1) determine
which interface is the most effective for the target users of
Mathsigner™ (e.g., children ages 5-11), and (2) identify any Gender
and Age differences in using the three interfaces. To accomplish
these goals we have designed an experiment consisting of a
cognitive walkthrough and a survey with rating questions. Sixteen
children ages 7-11 participated in the study, ten males and six
females. Results showed no significant interface effect on user task
performance (e.g., task completion time and number of errors);
however, interface differences were seen in rating of appeal, with
the animated interface rated more 'likeable' than the other two.
Task performance and rating of appeal were not affected
significantly by Gender or Age of the subjects.
Abstract: The occurrence of missing values in database is a serious problem for Data Mining tasks, responsible for degrading data quality and accuracy of analyses. In this context, the area has shown a lack of standardization for experiments to treat missing values, introducing difficulties to the evaluation process among different researches due to the absence in the use of common parameters. This paper proposes a testbed intended to facilitate the experiments implementation and provide unbiased parameters using available datasets and suited performance metrics in order to optimize the evaluation and comparison between the state of art missing values treatments.
Abstract: Rise/span ratio has been mentioned as one of the
reasons which contribute to the lower buckling load as compared to
the Classical theory buckling load but this ratio has not been quantified
in the equation. The purpose of this study was to determine a more
realistic buckling load by quantifying the effect of the rise/span ratio
because experiments have shown that the Classical theory
overestimates the load. The buckling load equation was derived based
on the theorem of work done and strain energy. Thereafter, finite
element modeling and simulation using ABAQUS was done to
determine the variables that determine the constant in the derived
equation. The rise/span was found to be the determining factor of the
constant in the buckling load equation. The derived buckling load
correlates closely to the load obtained from experiments.
Abstract: Web applications have become very complex and crucial, especially when combined with areas such as CRM (Customer Relationship Management) and BPR (Business Process Reengineering), the scientific community has focused attention to Web applications design, development, analysis, and testing, by studying and proposing methodologies and tools. This paper proposes an approach to automatic multi-dimensional concern mining for Web Applications, based on concepts analysis, impact analysis, and token-based concern identification. This approach lets the user to analyse and traverse Web software relevant to a particular concern (concept, goal, purpose, etc.) via multi-dimensional separation of concerns, to document, understand and test Web applications. This technique was developed in the context of WAAT (Web Applications Analysis and Testing) project. A semi-automatic tool to support this technique is currently under development.
Abstract: The nearly 21-year-old Jiujiang Bridge, which is suffering from uneven line shape, constant great downwarping of the main beam and cracking of the box girder, needs reinforcement and cable adjustment. It has undergone cable adjustment for twice with incomplete data. Therefore, the initial internal force state of the Jiujiang Bridge is identified as the key for the cable adjustment project. Based on parameter identification by means of static force test data, this paper suggests determining the initial internal force state of the cable-stayed bridge according to the cable force-displacement relationship parameter identification method. That is, upon measuring the displacement and the change in cable forces for twice, one can identify the parameters concerned by means of optimization. This method is applied to the cable adjustment, replacement and reinforcement project for the Jiujiang Bridge as a guidance for the cable adjustment and reinforcement project of the bridge.
Abstract: In studying the possibility of using plants as
rhizoremediators, barley and grass mixture which showed resistance
to various concentrations of oil were selected. The minimum
inhibitory effect of oil on these plants by morphological parameters
such as survival of plants, length and biomass of shoot and root
compared with the control was showed. In determining physiological
parameters, a slight decrease in the number of chlorophyll a and b in
the leaves of plants was noted. The differences in the ratio of the total
surface of the roots to the work surface with the growth of plants in
soil with oil in the study of adsorption of the root surface were
showed.
Abstract: This paper describes the evolution of language
politics and the part played by political leaders with reference to
the Dravidian parties in Tamil Nadu. It explores the interesting
evolution from separatism to coalition in sustaining the values of
parliamentary democracy and federalism. It seems that the
appropriation of language politics is fully ascribed to the DMK
leadership under Annadurai and Karunanidhi. For them, the Tamil
language is a self-determining power, a terrain of nationhood, and
a perennial source of social and political powers. The DMK
remains a symbol of Tamil nationalist party playing language
politics in the interest of the Tamils. Though electoral alliances
largely determine the success, the language politics still has
significant space in the politics of Tamil Nadu. Ironically, DMK
moves from the periphery to centre for getting national recognition
for the Tamils as well as for its own maximization of power. The
evolution can be seen in two major phases as: language politics for
party building; and language politics for state building with three
successive political processes, namely, language politics in the
process of separatism, representative politics and coalition. The
much pronounced Dravidian Movement is radical enough to
democratize the party ideology to survive the spirit of
parliamentary democracy. This has secured its own rewards in
terms of political power. The political power provides the means to
achieve the social and political goal of the political party.
Language politics and leadership pattern actualized this trend
though the movement is shifted from separatism to coalition.
Abstract: In this paper, we present a methodology for finding
authoritative researchers by analyzing academic Web sites. We show
a case study in which we concentrate on a set of Czech computer
science departments- Web sites. We analyze the relations between
them via hyperlinks and find the most important ones using several
common ranking algorithms. We then examine the contents of the
research papers present on these sites and determine the most
authoritative Czech authors.
Abstract: The main aim of this study is to identify the most
influential variables that cause defects on the items produced by a
casting company located in Turkey. To this end, one of the items
produced by the company with high defective percentage rates is
selected. Two approaches-the regression analysis and decision treesare
used to model the relationship between process parameters and
defect types. Although logistic regression models failed, decision tree
model gives meaningful results. Based on these results, it can be
claimed that the decision tree approach is a promising technique for
determining the most important process variables.
Abstract: Water quality is a subject of ongoing concern.
Deterioration of water quality has initiated serious management
efforts in many countries. This study endeavors to automatically
classify water quality. The water quality classes are evaluated using 6
factor indices. These factors are pH value (pH), Dissolved Oxygen
(DO), Biochemical Oxygen Demand (BOD), Nitrate Nitrogen
(NO3N), Ammonia Nitrogen (NH3N) and Total Coliform (TColiform).
The methodology involves applying data mining
techniques using multilayer perceptron (MLP) neural network
models. The data consisted of 11 sites of canals in Dusit district in
Bangkok, Thailand. The data is obtained from the Department of
Drainage and Sewerage Bangkok Metropolitan Administration
during 2007-2011. The results of multilayer perceptron neural
network exhibit a high accuracy multilayer perception rate at 96.52%
in classifying the water quality of Dusit district canal in Bangkok
Subsequently, this encouraging result could be applied with plan and
management source of water quality.
Abstract: Text data mining is a process of exploratory data
analysis. Classification maps data into predefined groups or classes.
It is often referred to as supervised learning because the classes are
determined before examining the data. This paper describes proposed
radial basis function Classifier that performs comparative crossvalidation
for existing radial basis function Classifier. The feasibility
and the benefits of the proposed approach are demonstrated by means
of data mining problem: direct Marketing. Direct marketing has
become an important application field of data mining. Comparative
Cross-validation involves estimation of accuracy by either stratified
k-fold cross-validation or equivalent repeated random subsampling.
While the proposed method may have high bias; its performance
(accuracy estimation in our case) may be poor due to high variance.
Thus the accuracy with proposed radial basis function Classifier was
less than with the existing radial basis function Classifier. However
there is smaller the improvement in runtime and larger improvement
in precision and recall. In the proposed method Classification
accuracy and prediction accuracy are determined where the
prediction accuracy is comparatively high.