Abstract: Fault-proneness of a software module is the
probability that the module contains faults. A correlation exists
between the fault-proneness of the software and the measurable
attributes of the code (i.e. the static metrics) and of the testing (i.e.
the dynamic metrics). Early detection of fault-prone software
components enables verification experts to concentrate their time and
resources on the problem areas of the software system under
development. This paper introduces Genetic Algorithm based
software fault prediction models with Object-Oriented metrics. The
contribution of this paper is that it has used Metric values of JEdit
open source software for generation of the rules for the classification
of software modules in the categories of Faulty and non faulty
modules and thereafter empirically validation is performed. The
results shows that Genetic algorithm approach can be used for
finding the fault proneness in object oriented software components.
Abstract: This paper presents a new strategy of identification
and classification of pathological voices using the hybrid method
based on wavelet transform and neural networks. After speech
acquisition from a patient, the speech signal is analysed in order to
extract the acoustic parameters such as the pitch, the formants, Jitter,
and shimmer. Obtained results will be compared to those normal and
standard values thanks to a programmable database. Sounds are
collected from normal people and patients, and then classified into
two different categories. Speech data base is consists of several
pathological and normal voices collected from the national hospital
“Rabta-Tunis". Speech processing algorithm is conducted in a
supervised mode for discrimination of normal and pathology voices
and then for classification between neural and vocal pathologies
(Parkinson, Alzheimer, laryngeal, dyslexia...). Several simulation
results will be presented in function of the disease and will be
compared with the clinical diagnosis in order to have an objective
evaluation of the developed tool.
Abstract: Knowledge-based e-mail systems focus on
incorporating knowledge management approach in order to enhance
the traditional e-mail systems. In this paper, we present a knowledgebased
e-mail system called KS-Mail where people do not only send
and receive e-mail conventionally but are also able to create a sense
of knowledge flow. We introduce semantic processing on the e-mail
contents by automatically assigning categories and providing links to
semantically related e-mails. This is done to enrich the knowledge
value of each e-mail as well as to ease the organization of the e-mails
and their contents. At the application level, we have also built
components like the service manager, evaluation engine and search
engine to handle the e-mail processes efficiently by providing the
means to share and reuse knowledge. For this purpose, we present the
KS-Mail architecture, and elaborate on the details of the e-mail
server and the application server. We present the ontology mapping
technique used to achieve the e-mail content-s categorization as well
as the protocols that we have developed to handle the transactions in
the e-mail system. Finally, we discuss further on the implementation
of the modules presented in the KS-Mail architecture.
Abstract: This paper was aimed to survey the level of awareness
of traditional grocery stores in Bangkok in these categories: location,
service quality, risk, shopping, worthwhile, shopping satisfaction, and
future shopping intention. The paper was also aimed to survey factors
influencing the decision to shop at traditional grocery stores in
Bangkok in the future. The findings revealed that consumers had a
high level of awareness of traditional grocery stores in Bangkok.
Consumers were aware that the price was higher and it was riskier to
buy goods and services at traditional grocery stores but they still had
a high level of preference to patronage traditional grocery stores. This
was due to the reasons that there was a high level of satisfaction from
the factors of the friendliness of the owner, the ability to negotiate the
price, the ability to buy on credit, free delivery, and the enjoyment to
meet with other customers in the same neighborhood.
Abstract: People have always needed to believe in some
supernatural power, which could explain nature phenomena.
Different kinds of religions like Christianity, Hinduism, Islam,
Buddhism have thought believers in all world, how to behave
themselves. We think the most important role of religion in modern
society most important role of religion in modern society is safety of
the People. World and traditional religion played a prominent role in
the socio-cultural progress, and in the development of man as a
spiritual being. At the heart of religious morals the belief in god and
responsibility before it lies and specifies religious and ethical values
and categories . The religion is based on ethical standards historically
developed by society, requirements and concepts, but it puts all
social and moral relations of the person in dependence on religious
values. For everything that the believer makes on a debt or a duty, he
bears moral responsibility before conscience, people and god. The
concept of value of religious morals takes the central place because
the religion from all forms of public consciousness most values is
painted as it is urged to answer vital questions. Any religion not only
considers questions of creation of the world, sense of human
existence, relationship of god and the person, but also offers the
ethical concept, develops rules of behavior of people. The religion a
long time dominated in the history of culture, and during this time
created a set of cultural and material values. The identity of Kazakh
culture can be defined as a Cultural identity traditional ,national
identity and the identity values developed by Kazakh people in
process of cultural-historical development, promoting formation of
Kazakh culture identity on public consciousness. Identity is the
historical process but always the tradition exists in it as a component
of stability, as a component of self that what this identity formed .
Abstract: Diagnostic goal of transformers in service is to detect the winding or the core in fault. Transformers are valuable equipment which makes a major contribution to the supply security of a power system. Consequently, it is of great importance to minimize the frequency and duration of unwanted outages of power transformers. So, Frequency Response Analysis (FRA) is found to be a useful tool for reliable detection of incipient mechanical fault in a transformer, by finding winding or core defects. The authors propose as first part of this article, the coupled circuits method, because, it gives most possible exhaustive modelling of transformers. And as second part of this work, the application of FRA in low frequency in order to improve and simplify the response reading. This study can be useful as a base data for the other transformers of the same categories intended for distribution grid.
Abstract: This paper looks at transgender identities and the law in the context of marriage. It particularly focuses on the role of language and definition in classifying transgendered individuals into a legal category. Two lines of cases in transgender jurisprudence are examined. The former cases decided the definition of 'man' and 'woman' on the basis of biological criteria while the latter cases held that biological factors should not be the sole criterion for defining a man or a woman. Three categories were found to classify transgender people, namely male, female and "monstrous". Since transgender people challenge the core gender distinction that the law stresses, they are often regarded as problematic and monstrous which caused them to be subjected to severe legal consequences. This paper discusses these issues by analyzing and comparing different cases in transgender jurisprudence as well as examining how these issues play out in contemporary Hong Kong.
Abstract: Character segmentation is an important preprocessing step for text recognition. In degraded documents, existence of touching characters decreases recognition rate drastically, for any optical character recognition (OCR) system. In this paper a study of touching Gurmukhi characters is carried out and these characters have been divided into various categories after a careful analysis.Structural properties of the Gurmukhi characters are used for defining the categories. New algorithms have been proposed to segment the touching characters in middle zone. These algorithms have shown a reasonable improvement in segmenting the touching characters in degraded Gurmukhi script. The algorithms proposed in this paper are applicable only to machine printed text.
Abstract: Classifying biomedical literature is a difficult and
challenging task, especially when a large number of biomedical
articles should be organized into a hierarchical structure. In this paper,
we present an approach for classifying a collection of biomedical text
abstracts downloaded from Medline database with the help of
ontology alignment. To accomplish our goal, we construct two types
of hierarchies, the OHSUMED disease hierarchy and the Medline
abstract disease hierarchies from the OHSUMED dataset and the
Medline abstracts, respectively. Then, we enrich the OHSUMED
disease hierarchy before adapting it to ontology alignment process for
finding probable concepts or categories. Subsequently, we compute
the cosine similarity between the vector in probable concepts (in the
“enriched" OHSUMED disease hierarchy) and the vector in Medline
abstract disease hierarchies. Finally, we assign category to the new
Medline abstracts based on the similarity score. The results obtained
from the experiments show the performance of our proposed approach
for hierarchical classification is slightly better than the performance of
the multi-class flat classification.
Abstract: Prediction of fault-prone modules provides one way to
support software quality engineering. Clustering is used to determine
the intrinsic grouping in a set of unlabeled data. Among various
clustering techniques available in literature K-Means clustering
approach is most widely being used. This paper introduces K-Means
based Clustering approach for software finding the fault proneness of
the Object-Oriented systems. The contribution of this paper is that it
has used Metric values of JEdit open source software for generation
of the rules for the categorization of software modules in the
categories of Faulty and non faulty modules and thereafter
empirically validation is performed. The results are measured in
terms of accuracy of prediction, probability of Detection and
Probability of False Alarms.
Abstract: The objective of this research was to study the career
success and the satisfaction of female executives working for schools
in Bangkok, Thailand. This paper drew upon the survey data
collected from 68 female executives. The survey conducted in on
Bangkok schools. The statistics utilized in this paper included
percentage, mean, standard deviation as well as t-test. The findings
revealed that the majority of samples had more than 30 years of
experience, held a master degree, and had an average income of less
than 40,000 baht. The majority of respondents worked not more than
50 hours per week. In addition, the mean score revealed career
development was ranked as their number one career satisfaction and
having a job related to education was ranked as their number one job
satisfaction. Also, the mean score of all categories of satisfaction was
4.61 with standard deviation of 1.677 which indicated that female
executive level of satisfaction was high. In terms of the subjectivity
career success, the hypothesis testing’s result disclosed that female
executives with different married status had a difference in their job
satisfaction which was significant at the 0.05 confidence level.
Abstract: Semnan is a city in semnan province, northern Iran
with a population estimated at 119,778 inhabitants. It is the
provincial capital of semnan province. Iran is a developing country
and construction is a basic factor of developing too. Hence, Semnan
city needs to a special programming for construction of buildings,
structures and infrastructures. Semnan municipality tries to begin this
program. In addition to, city has some historical monuments which
can be interesting for tourists. Hence, Semnan inhabitants can benefit
from tourist industry. Optimization of Energy in construction
industry is another activity of this municipality and the inhabitants
who execute these regulations receive some discounts. Many parts of
Iran such as semnan are located in highly seismic zones and
structures must be constructed safe e.g., according to recent seismic
codes. In this paper opportunities of IT in construction industry of
Iran are investigated in three categories. Pre-construction phase,
construction phase and earthquake disaster mitigation are studied.
Studies show that information technology can be used in these items
for reducing the losses and increasing the benefits. Both government
and private sectors must contribute to this strategic project for
obtaining the best result.
Abstract: Knowledge is a key asset for any organisation to
sustain competitive advantages, but it is difficult to identify and
represent knowledge which is needed to perform activities in
business processes. The effective knowledge management and
support for relevant business activities definitely gives a huge impact
to the performance of the organisation as a whole. This is because
that knowledge have the functions of directing, coordinating and
controlling actions within business processes. The study has
introduced organisational morphology, a norm-based approach by
applying semiotic theories which emphasise on the representation of
knowledge in norms. This approach is concerned with the
identification of activities into three categories: substantive,
communication and control activities. All activities are directed by
norms; hence three types of norms exist; each is associated to a
category of activities. The paper describes the approach briefly and
illustrates the application of this approach through a case study of
academic activities in higher education institutions. The result of the
study shows that the approach provides an effective way to profile
business knowledge and the profile enables the understanding and
specification of business requirements of an organisation.
Abstract: This paper is concerned with the production of an Arabic word semantic similarity benchmark dataset. It is the first of its kind for Arabic which was particularly developed to assess the accuracy of word semantic similarity measurements. Semantic similarity is an essential component to numerous applications in fields such as natural language processing, artificial intelligence, linguistics, and psychology. Most of the reported work has been done for English. To the best of our knowledge, there is no word similarity measure developed specifically for Arabic. In this paper, an Arabic benchmark dataset of 70 word pairs is presented. New methods and best possible available techniques have been used in this study to produce the Arabic dataset. This includes selecting and creating materials, collecting human ratings from a representative sample of participants, and calculating the overall ratings. This dataset will make a substantial contribution to future work in the field of Arabic WSS and hopefully it will be considered as a reference basis from which to evaluate and compare different methodologies in the field.
Abstract: Unintentional falls are rife throughout the ages and
have been the common factor of serious or critical injuries especially
for the elderly society. Fortunately, owing to the recent rapid
advancement in technology, fall detection system is made possible,
enabling detection of falling events for the elderly, monitoring the
patient and consequently provides emergency support in the event of
falling. This paper presents a review of 3 main categories of fall
detection techniques, ranging from year 2005 to year 2010. This
paper will be focusing on discussing the techniques alongside with
summary and conclusion for them.
Abstract: Malaysia government had been trying hard in order to
find the most efficient methods in learning. However, it is hard to
actually access and evaluate students whom will then be called an
excellent student. It is because in our realties student who excellent
is only excel in academic. This evaluation becomes a problem
because it not balances in our real life interm of to get an excellent
student in whole area in their involvement of curiculum and cocuriculum.
To overcome this scenario, we designed a module for
Student Idol to evaluate student through three categories which are
academic, co-curiculum and leadership. All the categories have their
own merit point. Using this method, student will be evaluated more
accurate compared to the previously. So, teacher can easily evaluate
their student without having any emotion factor, relation factor and
others. As conclusion this system module will helps the development
of student evaluation more accurate and valid in Student Idol.
Abstract: Searching similar documents and document
management subjects have important place in text mining. One of the
most important parts of similar document research studies is the
process of classifying or clustering the documents. In this study, a
similar document search approach that includes discussion of out the
case of belonging to multiple categories (multiple categories
problem) has been carried. The proposed method that based on Fuzzy
Similarity Classification (FSC) has been compared with Rocchio
algorithm and naive Bayes method which are widely used in text
mining. Empirical results show that the proposed method is quite
successful and can be applied effectively. For the second stage,
multiple categories vector method based on information of categories
regarding to frequency of being seen together has been used.
Empirical results show that achievement is increased almost two
times, when proposed method is compared with classical approach.
Abstract: The environmental performance of rapeseed oil (RO)
and rapeseed methyl ester(RME) from winter rape as fuels produced
in Romanian agroclimate is analyzed in this paper. The proposed
methodology is life cycle assessment (LCA) and takes into
consideration the influence of grain production and agroclimatic
conditions. This study shows favorable results first for RO and then
for RME. When compared to diesel fuel, both studied biofuels show
better results in the following impact categories: Abiotic depletion
potential (ADP), Ozone layer depletion (ODP) and Photochemical
ozone creation potential (POCP).Furthermore, the environmental
performance of the two biofuels studied can be improved by
changing the type of fertilizer used and also by using biofuels instead
of diesel in the field works.
Abstract: Caching was suggested as a solution for reducing bandwidth utilization and minimizing query latency in mobile environments. Over the years, different caching approaches have been proposed, some relying on the server to broadcast reports periodically informing of the updated data while others allowed the clients to request for the data whenever needed. Until recently a hybrid cache consistency scheme Scalable Asynchronous Cache Consistency Scheme SACCS was proposed, which combined the two different approaches benefits- and is proved to be more efficient and scalable. Nevertheless, caching has its limitations too, due to the limited cache size and the limited bandwidth, which makes the implementation of cache replacement strategy an important aspect for improving the cache consistency algorithms. In this thesis, we proposed a new cache replacement strategy, the Least Unified Value strategy (LUV) to replace the Least Recently Used (LRU) that SACCS was based on. This paper studies the advantages and the drawbacks of the new proposed strategy, comparing it with different categories of cache replacement strategies.
Abstract: The cellular network is one of the emerging areas of
communication, in which the mobile nodes act as member for one
base station. The cluster based communication is now an emerging
area of wireless cellular multimedia networks. The cluster renders
fast communication and also a convenient way to work with
connectivity. In our scheme we have proposed an optimization
technique for the fuzzy cluster nodes, by categorizing the group
members into three categories like long refreshable member, medium
refreshable member and short refreshable member. By considering
long refreshable nodes as static nodes, we compute the new
membership values for the other nodes in the cluster. We compare
their previous and present membership value with the threshold value
to categorize them into three different members. By which, we
optimize the nodes in the fuzzy clusters. The simulation results show
that there is reduction in the cluster computational time and
iterational time after optimization.