Abstract: While financial institutions have faced difficulties
over the years for a multitude of reasons, the major cause of serious
banking problems continues to be directly related to lax credit
standards for borrowers and counterparties, poor portfolio risk
management, or a lack of attention to changes in economic or other
circumstances that can lead to a deterioration in the credit standing of
a bank's counterparties. Credit risk is most simply defined as the
potential that a bank borrower or counterparty will fail to meet its
obligations in accordance with agreed terms. The goal of credit risk
management is to maximize a bank's risk-adjusted rate of return by
maintaining credit risk exposure within acceptable parameters. Banks
need to manage the credit risk inherent in the entire portfolio as well
as the risk in individual credits or transactions. Banks should also
consider the relationships between credit risk and other risks. The
effective management of credit risk is a critical component of a
comprehensive approach to risk management and essential to the
long-term success of any banking organization. In this research we
also study the relationship between credit risk indices and borrower-s
timely payback in Karafarin bank.
Abstract: A computer model of Quantum Theory (QT) has been
developed by the author. Major goal of the computer model was
support and demonstration of an as large as possible scope of QT.
This includes simulations for the major QT (Gedanken-) experiments
such as, for example, the famous double-slit experiment.
Besides the anticipated difficulties with (1) transforming exacting
mathematics into a computer program, two further types of problems
showed up, namely (2) areas where QT provides a complete mathematical
formalism, but when it comes to concrete applications the
equations are not solvable at all, or only with extremely high effort;
(3) QT rules which are formulated in natural language and which do
not seem to be translatable to precise mathematical expressions, nor
to a computer program.
The paper lists problems in all three categories and describes also
the possible solutions or circumventions developed for the computer
model.
Abstract: In today-s new technology era, cluster has become a
necessity for the modern computing and data applications since many
applications take more time (even days or months) for computation.
Although after parallelization, computation speeds up, still time
required for much application can be more. Thus, reliability of the
cluster becomes very important issue and implementation of fault
tolerant mechanism becomes essential. The difficulty in designing a
fault tolerant cluster system increases with the difficulties of various
failures. The most imperative obsession is that the algorithm, which
avoids a simple failure in a system, must tolerate the more severe
failures. In this paper, we implemented the theory of watchdog timer
in a parallel environment, to take care of failures. Implementation of
simple algorithm in our project helps us to take care of different
types of failures; consequently, we found that the reliability of this
cluster improves.
Abstract: In this paper we propose a computational model for the representation and processing of morpho-phonological phenomena in a natural language, like Modern Greek. We aim at a unified treatment of inflection, compounding, and word-internal phonological changes, in a model that is used for both analysis and generation. After discussing certain difficulties cuase by well-known finitestate approaches, such as Koskenniemi-s two-level model [7] when applied to a computational treatment of compounding, we argue that a morphology-based model provides a more adequate account of word-internal phenomena. Contrary to the finite state approaches that cannot handle hierarchical word constituency in a satisfactory way, we propose a unification-based word grammar, as the nucleus of our strategy, which takes into consideration word representations that are based on affixation and [stem stem] or [stem word] compounds. In our formalism, feature-passing operations are formulated with the use of the unification device, and phonological rules modeling the correspondence between lexical and surface forms apply at morpheme boundaries. In the paper, examples from Modern Greek illustrate our approach. Morpheme structures, stress, and morphologically conditioned phoneme changes are analyzed and generated in a principled way.
Abstract: In Knowledge Structure Graph, each course unit
represents a phase of learning activities. Both learning portfolios and
Knowledge Structure Graphs contain learning information of students
and let teachers know which content are difficulties and fails. The
study purposes "Dual Mode On-line Learning Diagnosis System" that
integrates two search methods: learning portfolio and knowledge
structure. Teachers can operate the proposed system and obtain the
information of specific students without any computer science
background. The teachers can find out failed students in advance and
provide remedial learning resources.
Abstract: The new framework the Higher Education is
immersed in involves a complete change in the way lecturers must
teach and students must learn. Whereas the lecturer was the main
character in traditional education, the essential goal now is to
increase the students' participation in the process. Thus, one of the
main tasks of lecturers in this new context is to design activities of
different nature in order to encourage such participation. Seminars
are one of the activities included in this environment. They are active
sessions that enable going in depth into specific topics as support of
other activities. They are characterized by some features such as
favoring interaction between students and lecturers or improving
their communication skills. Hence, planning and organizing strategic
seminars is indeed a great challenge for lecturers with the aim of
acquiring knowledge and abilities. This paper proposes a method
using Artificial Intelligence techniques to obtain student profiles
from their marks and preferences. The goal of building such profiles
is twofold. First, it facilitates the task of splitting the students into
different groups, each group with similar preferences and learning
difficulties. Second, it makes it easy to select adequate topics to be a
candidate for the seminars. The results obtained can be either a
guarantee of what the lecturers could observe during the development
of the course or a clue to reconsider new methodological strategies in
certain topics.
Abstract: Sickness absence represents a major economic and
social issue. Analysis of sick leave data is a recurrent challenge to analysts because of the complexity of the data structure which is
often time dependent, highly skewed and clumped at zero. Ignoring these features to make statistical inference is likely to be inefficient
and misguided. Traditional approaches do not address these problems. In this study, we discuss model methodologies in terms of statistical techniques for addressing the difficulties with sick leave data. We also introduce and demonstrate a new method by performing a longitudinal assessment of long-term absenteeism using
a large registration dataset as a working example available from the Helsinki Health Study for municipal employees from Finland during the period of 1990-1999. We present a comparative study on model
selection and a critical analysis of the temporal trends, the occurrence
and degree of long-term sickness absences among municipal employees. The strengths of this working example include the large
sample size over a long follow-up period providing strong evidence in supporting of the new model. Our main goal is to propose a way to
select an appropriate model and to introduce a new methodology for analysing sickness absence data as well as to demonstrate model
applicability to complicated longitudinal data.
Abstract: The practical implementation of audio-video coupled speech recognition systems is mainly limited by the hardware complexity to integrate two radically different information capturing devices with good temporal synchronisation. In this paper, we propose a solution based on a smart CMOS image sensor in order to simplify the hardware integration difficulties. By using on-chip image processing, this smart sensor can calculate in real time the X/Y projections of the captured image. This on-chip projection reduces considerably the volume of the output data. This data-volume reduction permits a transmission of the condensed visual information via the same audio channel by using a stereophonic input available on most of the standard computation devices such as PC, PDA and mobile phones. A prototype called VMIKE (Visio-Microphone) has been designed and realised by using standard 0.35um CMOS technology. A preliminary experiment gives encouraged results. Its efficiency will be further investigated in a large variety of applications such as biometrics, speech recognition in noisy environments, and vocal control for military or disabled persons, etc.
Abstract: The research investigates the “impact of VLE on mathematical concepts acquisition of the special education needs (SENs) students at KS4 secondary education sector" in England. The overall aim of the study is to establish possible areas of difficulties to approach for above or below knowledge standard requirements for KS4 students in the acquisition and validation of basic mathematical concepts. A teaching period, in which virtual learning environment (Fronter) was used to emphasise different mathematical perception and symbolic representation was carried out and task based survey conducted to 20 special education needs students [14 actually took part]. The result shows that students were able to process information and consider images, objects and numbers within the VLE at early stages of acquisition process. They were also able to carry out perceptual tasks but with limiting process of different quotient, thus they need teacher-s guidance to connect them to symbolic representations and sometimes coach them through. The pilot study further indicates that VLE curriculum approaches for students were minutely aligned with mathematics teaching which does not emphasise the integration of VLE into the existing curriculum and current teaching practice. There was also poor alignment of vision regarding the use of VLE in realisation of the objectives of teaching mathematics by the management. On the part of teacher training, not much was done to develop teacher-s skills in the technical and pedagogical aspects of VLE that is in-use at the school. The classroom observation confirmed teaching practice will find a reliance on VLE as an enhancer of mathematical skills, providing interaction and personalisation of learning to SEN students.
Abstract: Identity verification of authentic persons by their multiview faces is a real valued problem in machine vision. Multiview faces are having difficulties due to non-linear representation in the feature space. This paper illustrates the usability of the generalization of LDA in the form of canonical covariate for face recognition to multiview faces. In the proposed work, the Gabor filter bank is used to extract facial features that characterized by spatial frequency, spatial locality and orientation. Gabor face representation captures substantial amount of variations of the face instances that often occurs due to illumination, pose and facial expression changes. Convolution of Gabor filter bank to face images of rotated profile views produce Gabor faces with high dimensional features vectors. Canonical covariate is then used to Gabor faces to reduce the high dimensional feature spaces into low dimensional subspaces. Finally, support vector machines are trained with canonical sub-spaces that contain reduced set of features and perform recognition task. The proposed system is evaluated with UMIST face database. The experiment results demonstrate the efficiency and robustness of the proposed system with high recognition rates.
Abstract: To understand complex living system an effort has
made by mechanical engineers and dentists to deliver prompt
products and services to patients concerned about their aesthetic look.
Since two decades various bracket systems have designed involving
techniques like milling, injection molding which are technically not
flexible for the customized dental product development. The aim of
this paper to design, develop a customized system which is
economical and mainly emphasizes the expertise design and
integration of engineering and dental fields. A custom made selfadjustable
lingual bracket and customized implants are designed and
developed using computer aided design (CAD) and rapid prototyping
technology (RPT) to improve the smiles and to overcome the
difficulties associated with conventional ones. Lengthy orthodontic
treatment usually not accepted by the patients because the patient
compliance is lost. Patient-s compliance can be improved by
facilitating faster tooth movements by designing a localized dental
vibrator using advanced engineering principles.
Abstract: The Automatic Speech Recognition (ASR) applied to
Arabic language is a challenging task. This is mainly related to the
language specificities which make the researchers facing multiple
difficulties such as the insufficient linguistic resources and the very
limited number of available transcribed Arabic speech corpora. In
this paper, we are interested in the development of a HMM-based
ASR system for Standard Arabic (SA) language. Our fundamental
research goal is to select the most appropriate acoustic parameters
describing each audio frame, acoustic models and speech recognition
unit. To achieve this purpose, we analyze the effect of varying frame
windowing (size and period), acoustic parameter number resulting
from features extraction methods traditionally used in ASR, speech
recognition unit, Gaussian number per HMM state and number of
embedded re-estimations of the Baum-Welch Algorithm. To evaluate
the proposed ASR system, a multi-speaker SA connected-digits
corpus is collected, transcribed and used throughout all experiments.
A further evaluation is conducted on a speaker-independent continue
SA speech corpus. The phonemes recognition rate is 94.02% which is
relatively high when comparing it with another ASR system
evaluated on the same corpus.
Abstract: In this paper, we construct and implement a new
Steganography algorithm based on learning system to hide a large
amount of information into color BMP image. We have used adaptive
image filtering and adaptive non-uniform image segmentation with
bits replacement on the appropriate pixels. These pixels are selected
randomly rather than sequentially by using new concept defined by
main cases with sub cases for each byte in one pixel. According to
the steps of design, we have been concluded 16 main cases with their
sub cases that covere all aspects of the input information into color
bitmap image. High security layers have been proposed through four
layers of security to make it difficult to break the encryption of the
input information and confuse steganalysis too. Learning system has
been introduces at the fourth layer of security through neural
network. This layer is used to increase the difficulties of the statistical
attacks. Our results against statistical and visual attacks are discussed
before and after using the learning system and we make comparison
with the previous Steganography algorithm. We show that our
algorithm can embed efficiently a large amount of information that
has been reached to 75% of the image size (replace 18 bits for each
pixel as a maximum) with high quality of the output.
Abstract: The complex structure of lignocellulose leads to great
difficulties in converting it to fermentable sugars for the ethanol
production. The major hydrolysis impediments are the crystallinity of
cellulose and the lignin content. To improve the efficiency of
enzymatic hydrolysis, microbial pretreatment of corncob was
investigated using two bacterial strains of Bacillus subtilis A 002 and
Cellulomonas sp. TISTR 784 (expected to break open the crystalline
part of cellulose) and lignin-degrading fungus, Phanerochaete
sordida SK7 (expected to remove lignin from lignocellulose). The
microbial pretreatment was carried out with each strain under its
optimum conditions. The pretreated corncob samples were further
hydrolyzed to produce reducing glucose with low amounts of
commercial cellulase (25 U·g-1 corncob) from Aspergillus niger. The
corncob samples were determined for composition change by X-ray
diffraction (XRD), Fourier transform infrared spectroscopy (FTIR),
and scanning electron microscope (SEM). According to the results,
the microbial pretreatment with fungus, P. sordida SK7 was the most
effective for enhancing enzymatic hydrolysis, approximately, 40%
improvement.
Abstract: In this work, we consider an application of neural networks in LD converter. Application of this approach assumes a reliable prediction of steel temperature and reduces a reblow ratio in steel work. It has been applied a conventional model to charge calculation, the obtained results by this technique are not always good, this is due to the process complexity. Difficulties are mainly generated by the noisy measurement and the process non linearities. Artificial Neural Networks (ANNs) have become a powerful tool for these complex applications. It is used a backpropagation algorithm to learn the neural nets. (ANNs) is used to predict the steel bath temperature in oxygen converter process for the end condition. This model has 11 inputs process variables and one output. The model was tested in steel work, the obtained results by neural approach are better than the conventional model.
Abstract: This work represents the first review paper to explore the relationship between perfectionistic personality and borderline personality organization. The developmental origins, identity diffusion, interpersonal difficulties, and defense mechanisms that are common to both borderline personality and the interpersonal components of perfectionism are explored, and existing research on perfectionism and borderline personality is reviewed. The importance of the link between perfectionism and borderline features is discussed in terms of its contribution to the conceptual understanding of personality pathology as well as to applied clinical practices.
Abstract: There have been significant improvements in automatic
voice recognition technology. However, existing systems still face difficulties,
particularly when used by non-native speakers with accents.
In this paper we address a problem of identifying the English accented
speech of speakers from different backgrounds. Once an accent is
identified the speech recognition software can utilise training set from
appropriate accent and therefore improve the efficiency and accuracy
of the speech recognition system. We introduced the Q factor, which
is defined by the sum of relationships between frequencies of the
formants. Four different accents were considered and experimented
for this research. A scoring method was introduced in order to
effectively analyse accents. The proposed concept indicates that the
accent could be identified by analysing their formants.
Abstract: In current global economics the application of Business Continuity Management is the prerequisite for sustainable competitive advantage in an organization. Business Continuity Management is a managerial which identifies the potential impact of losses in an organization. The aim of this paper is to identify and critically evaluate the relative advantages and disadvantages of deploying Business Continuity Management in an organization on the basis of seven criteria. The strongest advantage of Business Continuity Management is in its capacity to identify a crisis situation and help the organization to flexibly and also to keep the critical knowledge within the organization. By contrast the main disadvantage is that establishing Business Continuity Management in an organization is time-consuming and its implementation as an integral part of the organizational culture present significant difficulties.
Abstract: Two-dimensional (2D) bar codes were designed to
carry significantly more data with higher information density and
robustness than its 1D counterpart. Thanks to the popular
combination of cameras and mobile phones, it will naturally bring
great commercial value to use the camera phone for 2D bar code
reading. This paper addresses the problem of specific 2D bar code
design for mobile phones and introduces a low-level encoding
method of matrix codes. At the same time, we propose an efficient
scheme for 2D bar codes decoding, of which the effort is put on
solutions of the difficulties introduced by low image quality that is
very common in bar code images taken by a phone camera.
Abstract: A straightforward and intuitive combination of single simulations into an aggregated master-simulation is not trivial. There are lots of problems, which trigger-specific difficulties during the modeling and execution of such a simulation. In this paper we identify these problems and aim to solve them by mapping the task to the field of multi agent systems. The solution is a new meta-model named AGENTMAP, which is able to mitigate most of the problems and to support intuitive modeling at the same time. This meta-model will be introduced and explained on basis of an example from the e-commerce domain.