Abstract: It has become crucial over the years for nations to
improve their credit scoring methods and techniques in light of the
increasing volatility of the global economy. Statistical methods or
tools have been the favoured means for this; however artificial
intelligence or soft computing based techniques are becoming
increasingly preferred due to their proficient and precise nature and
relative simplicity. This work presents a comparison between Support
Vector Machines and Artificial Neural Networks two popular soft
computing models when applied to credit scoring. Amidst the
different criteria-s that can be used for comparisons; accuracy,
computational complexity and processing times are the selected
criteria used to evaluate both models. Furthermore the German credit
scoring dataset which is a real world dataset is used to train and test
both developed models. Experimental results obtained from our study
suggest that although both soft computing models could be used with
a high degree of accuracy, Artificial Neural Networks deliver better
results than Support Vector Machines.
Abstract: This paper is concerned with propagation of thermoelastic longitudinal vibrations of an infinite circular cylinder, in the context of the linear theory of generalized thermoelasticity with two relaxation time parameters (Green and Lindsay theory). Three displacement potential functions are introduced to uncouple the equations of motion. The frequency equation, by using the traction free boundary conditions, is given in the form of a determinant involving Bessel functions. The roots of the frequency equation give the value of the characteristic circular frequency as function of the wave number. These roots, which correspond to various modes, are numerically computed and presented graphically for different values of the thermal relaxation times. It is found that the influences of the thermal relaxation times on the amplitudes of the elastic and thermal waves are remarkable. Also, it is shown in this study that the propagation of thermoelastic longitudinal vibrations based on the generalized thermoelasticity can differ significantly compared with the results under the classical formulation. A comparison of the results for the case with no thermal effects shows well agreement with some of the corresponding earlier results.
Abstract: Social cognitive theory explains the power to inaugurate change is determined by the mutual influence of personal proclivity and social factors which will shape ones- motivations and expectations. In construction industry, green concept offers an opportunity to leave a lighter footprint on the environment. This opportunity, however, has not been fully grasped by many countries. As such, venturing into green construction for many practitioners would be their maiden experience. Decision to venture into new practice such as green construction will be influenced by certain drivers. This paper explores these drivers which is further expanded into motivational factors and later becomes the platform upon which expectation for green construction stands. This theoretical concept of motivation and expectations, which is adapted from social cognitive theory, focus on developers- view because of their crucial role in green application. This conceptual framework, which serves as the basis for further research, will benefit the industry as it elucidate cognitive angles to attract more new entrants to green business.
Abstract: DG application has received increasing attention during
recent years. The impact of DG on various aspects of distribution system
operation, such as reliability and energy loss, depend highly on DG
location in distribution feeder. Optimal DG placement is an important
subject which has not been fully discussed yet.
This paper presents an optimization method to determine optimal DG
placement, based on a cost/worth analysis approach. This method
considers technical and economical factors such as energy loss, load point
reliability indices and DG costs, and particularly, portability of DG. The
proposed method is applied to a test system and the impacts of different
parameters such as load growth rate and load forecast uncertainty (LFU)
on optimum DG location are studied.
Abstract: In view of geological origin, formation of the shallow
gas reservoir of the Hangzhou Bay, northern Zhejiang Province,
eastern China, and original occurrence characteristics of the gassy
sand are analyzed. Generally, gassy sand in scale gas reservoirs is in
the state of residual moisture content and the approximate scope of
initial matric suction of sand ranges about from 0kPa to100kPa.
Results based on GDS triaxial tests show that the classical shear
strength formulas of unsaturated soil can not effectively describe basic
strength characteristics of gassy sand; the relationship between
apparent cohesion and matric suction of gassy sand agrees well with
the power function, which can reasonably be used to describe the
strength of gassy sand. In the stress path of gas release, shear strength
of gassy sand will increase and experimental results show the formula
proposed in this paper can effectively predict the strength increment.
When saturated strength indexes of the sand are used in engineering
design, moderate reduction should be considered.
Abstract: An attempt was made to study of nitrogen
components response of corn (Zea mays L.) to drought stress. A farm
research was done in RCBD as split-plot with four replications in
Khorramabad, west Iran. Drought stress levels as irrigation regimes
after 75 (control), 100, and 120 (stress) mm cumulative evaporation
were in main plots, and four seed corn varieties include 500 (medium
maturity), 647, 700, and 704 (long maturity) were as subplots.
Soluble protein, nitrate and proline amino acid were measured in
shoot and root at flowering stage, and grain yield was measured in
harvesting stage. As the drought progressed, the amount of nitrate
and proline followed an increasing trend, but soluble protein
decreased in shoot and root. The highest amount of nitrate and
proline was observed in longer maturity varieties than shorter ones,
but decrease yield of long maturity varieties was higher than medium
maturity varieties in drought condition, because of long duration of
stress.
Abstract: Environmental micro-organisms include a large number of taxa and some species that are generally considered nonpathogenic, but can represent a risk in certain conditions, especially for elderly people and immunocompromised individuals. Chemotaxonomic identification techniques are powerful tools for environmental micro-organisms, and cellular fatty acid methyl esters (FAME) content is a powerful fingerprinting identification technique. A system based on an unsupervised artificial neural network (ANN) was set up using the fatty acid profiles of standard bacterial strains, obtained by gas-chromatography, used as learning data. We analysed 45 certified strains belonging to Acinetobacter, Aeromonas, Alcaligenes, Aquaspirillum, Arthrobacter, Bacillus, Brevundimonas, Enterobacter, Flavobacterium, Micrococcus, Pseudomonas, Serratia, Shewanella and Vibrio genera. A set of 79 bacteria isolated from a drinking water line (AMGA, the major water supply system in Genoa) were used as an example for identification compared to standard MIDI method. The resulting ANN output map was found to be a very powerful tool to identify these fresh isolates.
Abstract: With the rapid growth and development of information and communication technology, the Internet has played a definite and irreplaceable role in people-s social lives in Taiwan like in other countries. In July 2008, on a general social website, an unexpected phenomenon was noticed – that there were more than one hundred users who started forming clubs voluntarily and having face-to-face gatherings for specific purposes. In this study, it-s argued whether or not teenagers- social contact on the Internet is involved in their life context, and tried to reveal the teenagers- social preferences, values, and needs, which merge with and influence teenagers- social activities. Therefore, the study conducts multiple user experience research methods, which include practical observations and qualitative analysis by contextual inquiries and in-depth interviews. Based on the findings, several design implications for software related to social interactions and cultural inheritance are offered. It is concluded that the inherent values of a social behaviors might be a key issue in developing computer-mediated communication or interaction designs in the future.
Abstract: In the last 15 years, a number of methods have been proposed for forecasting based on fuzzy time series. Most of the fuzzy time series methods are presented for forecasting of enrollments at the University of Alabama. However, the forecasting accuracy rates of the existing methods are not good enough. In this paper, we compared our proposed new method of fuzzy time series forecasting with existing methods. Our method is based on frequency density based partitioning of the historical enrollment data. The proposed method belongs to the kth order and time-variant methods. The proposed method can get the best forecasting accuracy rate for forecasting enrollments than the existing methods.
Abstract: In face recognition, feature extraction techniques
attempts to search for appropriate representation of the data. However,
when the feature dimension is larger than the samples size, it brings
performance degradation. Hence, we propose a method called
Normalization Discriminant Independent Component Analysis
(NDICA). The input data will be regularized to obtain the most
reliable features from the data and processed using Independent
Component Analysis (ICA). The proposed method is evaluated on
three face databases, Olivetti Research Ltd (ORL), Face Recognition
Technology (FERET) and Face Recognition Grand Challenge
(FRGC). NDICA showed it effectiveness compared with other
unsupervised and supervised techniques.
Abstract: Measuring the complexity of software has been an
insoluble problem in software engineering. Complexity measures can
be used to predict critical information about testability, reliability,
and maintainability of software systems from automatic analysis of
the source code. During the past few years, many complexity
measures have been invented based on the emerging Cognitive
Informatics discipline. These software complexity measures,
including cognitive functional size, lend themselves to the approach
of the total cognitive weights of basic control structures such as loops
and branches. This paper shows that the current existing calculation
method can generate different results that are algebraically
equivalence. However, analysis of the combinatorial meanings of this
calculation method shows significant flaw of the measure, which also
explains why it does not satisfy Weyuker's properties. Based on the
findings, improvement directions, such as measures fusion, and
cumulative variable counting scheme are suggested to enhance the
effectiveness of cognitive complexity measures.
Abstract: Changing in consumers lifestyles and food
consumption patterns provide a great opportunity in developing the
functional food sector in Malaysia. There is only a little knowledge
about whether Malaysian consumers are aware of functional food and
if so what image consumers have of this product. The objective of
this research is to determine the extent to which selected socioeconomic
characteristics and attitudes influence consumers-
awareness of functional food. A survey was conducted in the Klang
Valley, Malaysia where 439 respondents were interviewed using a
structured questionnaire. The result shows that most respondents
have a positive attitude towards functional food. For the binary
logistic estimation, the results indicate that age, income and other
factors such as concern about food safety, subscribing to cooking or
health magazines, being a vegetarian and consumers who have been
involved in a food production company significantly influence
Malaysian consumers- awareness towards functional food.
Abstract: The experiment was conducted to study the effect of
rearing systems on fatty acid composition and cholesterol content of
Thai indigenous chicken meat. Three hundred and sixty chicks were
allocated to 2 different rearing systems: conventional, housing in an
indoor pen (5 birds/m2); free-range, housing in an indoor pen (5
birds/m2) with access to a grass paddock (1 bird/m2) from 8 wk of age
until slaughter. All birds were provided with the same diet during the
experimental period. At 16 wk of age, 24 birds per group were
slaughtered to evaluate the fatty acid composition and cholesterol
content of breast and thigh meat. The results showed that the
proportion of SFA, MUFA and PUFA in breast and thigh meat were
not different among groups (P>0.05). However, the proportion of n-3
fatty acids was higher and the ratio of n-6 to n-3 fatty acids was lower
in free-range system than in conventional system (P0.05). The data indicated that the free-range system
could increase the proportion of n-3 fatty acids, but no effect on
cholesterol content in Thai indigenous chicken meat.
Abstract: Weblogs are resource of social structure to discover and track the various type of information written by blogger. In this paper, we proposed to use mining weblogs technique for identifying the trends of influenza where blogger had disseminated their opinion for the anomaly disease. In order to identify the trends, web crawler is applied to perform a search and generated a list of visited links based on a set of influenza keywords. This information is used to implement the analytics report system for monitoring and analyzing the pattern and trends of influenza (H1N1). Statistical and graphical analysis reports are generated. Both types of the report have shown satisfactory reports that reflect the awareness of Malaysian on the issue of influenza outbreak through blogs.
Abstract: One of the basic concepts in marketing is the concept
of meeting customers- needs. Since customer satisfaction is essential
for lasting survival and development of a business, screening and
observing customer satisfaction and recognizing its underlying
factors must be one of the key activities of every business.
The purpose of this study is to recognize the drivers that effect
customer satisfaction in a business-to-business situation in order to
improve marketing activities. We conducted a survey in which 93
business customers of a manufacturer of Diesel Generator in Iran
participated and they talked about their ideas and satisfaction of
supplier-s services related to its products. We developed the measures
for drivers of satisfaction first by as investigative research (by means
of feedback from executives and customers of sponsoring firm). Then
based on these measures, we created a mail survey, and asked the
respondents to explain their opinion about the sponsoring firm which
was a supplier of diesel generator and similar products. Furthermore,
the survey required the participants to mention their functional areas
and their company features.
In Conclusion we found that there are three drivers for customer
satisfaction, which are reliability, information about product, and
commercial features. Buyers/users from different functional areas
attribute different degree of importance to the last two drivers. For
instance, people from buying and management areas believe that
commercial features are more important than information about
products. But people in engineering, maintenance and production
areas believe that having information about products is more
important than commercial aspects. Marketing experts should
consider the attribute of customers regarding information about the
product and commercial features to improve market share.
Abstract: This paper proposes a delay-dependent leader-following consensus condition of multi-agent systems with both communication delay and probabilistic self-delay. The proposed methods employ a suitable piecewise Lyapunov-Krasovskii functional and the average dwell time approach. New consensus criterion for the systems are established in terms of linear matrix inequalities (LMIs) which can be easily solved by various effective optimization algorithms. Numerical example showed that the proposed method is effective.
Abstract: Recommender Systems act as personalized decision
guides, aiding users in decisions on matters related to personal taste.
Most previous research on Recommender Systems has focused on the
statistical accuracy of the algorithms driving the systems, with no
emphasis on the trustworthiness of the user. RS depends on
information provided by different users to gather its knowledge. We
believe, if a large group of users provide wrong information it will
not be possible for the RS to arrive in an accurate conclusion. The
system described in this paper introduce the concept of Testing the
knowledge of user to filter out these “bad users".
This paper emphasizes on the mechanism used to provide robust
and effective recommendation.
Abstract: This research tries to analyze the role that knowledge
about foreign markets has in increasing firms- exports in clustered
spaces. We consider two interrelated sources of knowledge: firms-
direct experience and indirect experience from other clustered firms –
export externalities. In particular, it is proposed that firms would
improve their export performance by accessing to export externalities
if they have some previous direct experience that allows them to
identify, understand and exploit them. Also, we propose that this
positive influence of previous direct experience on export
externalities keeps only up to a point, where it becomes negative,
creating an inverted “U" shape. Empirical evidence gathered among
wine producers located in La Rioja tends to confirm that firms enjoy
of export externalities if they have export experience along several
years and countries increase their export performance. While this
relationship becomes less relevant as they develop a higher
experience, we could not confirm the existence of a curvilinear
relationship in their influence on export externalities and export
performance.
Abstract: Computer modeling has played a unique role in
understanding electrocardiography. Modeling and simulating cardiac
action potential propagation is suitable for studying normal and
pathological cardiac activation. This paper presents a 2-D Cellular
Automata model for simulating action potential propagation in
cardiac tissue. We demonstrate a novel algorithm in order to use
minimum neighbors. This algorithm uses the summation of the
excitability attributes of excited neighboring cells. We try to
eliminate flat edges in the result patterns by inserting probability to
the model. We also preserve the real shape of action potential by
using linear curve fitting of one well known electrophysiological
model.
Abstract: In the last years, the computers have increased their capacity of calculus and networks, for the interconnection of these machines. The networks have been improved until obtaining the actual high rates of data transferring. The programs that nowadays try to take advantage of these new technologies cannot be written using the traditional techniques of programming, since most of the algorithms were designed for being executed in an only processor,in a nonconcurrent form instead of being executed concurrently ina set of processors working and communicating through a network.This paper aims to present the ongoing development of a new system for the reconfiguration of grouping of computers, taking into account these new technologies.