Abstract: This paper aims to analyze the role of natural
language processing (NLP). The paper will discuss the role in the
context of automated data retrieval, automated question answer, and
text structuring. NLP techniques are gaining wider acceptance in real
life applications and industrial concerns. There are various
complexities involved in processing the text of natural language that
could satisfy the need of decision makers. This paper begins with the
description of the qualities of NLP practices. The paper then focuses
on the challenges in natural language processing. The paper also
discusses major techniques of NLP. The last section describes
opportunities and challenges for future research.
Abstract: The financial crises caused a collapse in prices of
most asset classes, raising the attention on alternative investments
such as sukuk, a smaller, fast growing but often misunderstood
market. We study diversification benefits of sukuk, their correlation
with other asset classes and the effects of their inclusion in
investment portfolios of institutional and retail investors, through a
comprehensive comparison of their risk/return profiles during and
after the financial crisis.
We find a beneficial performance adjusted for the specific
volatility together with a lower correlation especially during the
financial crisis. The distribution of sukuk returns is positively skewed
and leptokurtic, with a risk/return profile similarly to high yield
bonds. Overall, our results suggest that sukuk present diversification
opportunities, a significant volatility-adjusted performance and lower
correlations especially during the financial crisis.
Our findings are relevant for a number of institutional investors.
Long term investors, such as life insurers would benefit from sukuk’s
protective features during financial crisis yet keeping return and
growth opportunities, whereas banks would gain due to their role of
placers, advisors, market makers or underwriters.
Abstract: Regardless of the manufacturing process used,
subtractive or additive, material, purpose and application, produced
components are conventionally solid mass with more or less complex
shape depending on the production technology selected. Aspects
such as reducing the weight of components, associated with the low
volume of material required and the almost non-existent material
waste, speed and flexibility of production and, primarily, a high
mechanical strength combined with high structural performance, are
competitive advantages in any industrial sector, from automotive,
molds, aviation, aerospace, construction, pharmaceuticals, medicine
and more recently in human tissue engineering. Such features,
properties and functionalities are attained in metal components
produced using the additive technique of Rapid Prototyping from
metal powders commonly known as Selective Laser Melting (SLM),
with optimized internal topologies and varying densities. In order to
produce components with high strength and high structural and
functional performance, regardless of the type of application, three
different internal topologies were developed and analyzed using
numerical computational tools. The developed topologies were
numerically submitted to mechanical compression and four point
bending testing. Finite Element Analysis results demonstrate how
different internal topologies can contribute to improve mechanical
properties, even with a high degree of porosity relatively to fully
dense components. Results are very promising not only from the
point of view of mechanical resistance, but especially through the
achievement of considerable variation in density without loss of
structural and functional high performance.
Abstract: The paper follows a discourse on computer-assisted
language learning. We examine problems of foreign language
teaching and learning and introduce a metamodel that can be used to
define learning models of language grammar structures in order to
support teacher/student interaction. Special attention is paid to the
concept of a virtual language lab. Our approach to language
education assumes to encourage learners to experiment with a
language and to learn by discovering patterns of grammatically
correct structures created and managed by a language expert.
Abstract: This paper reviews the internal use of blogs and their
potential effectiveness as organisational learning tools. Since the
emergence of the concept of ‘Enterprise 2.0’ there remains a lack of
empirical evidence associated with how organisations are applying
social media tools and whether they are effective towards supporting
organisational learning. Surprisingly, blogs, one of the more
traditional social media tools, still remains under-researched in the
context of ‘Enterprise 2.0’ and organisational learning. The aim of
this paper is to identify the theoretical linkage between blogs and
organisational learning in addition to reviewing prior research on
organisational blogging exploring why this area remains underresearched.
Through a literature review, one of the principal findings
of this paper is that organisational blogs have a mutual compatibility
with the interpretivist aspect of organisational learning. This paper
further advocates that further empirical work in this subject area is
required to substantiate this theoretical assumption.
Abstract: The electric power supplied by a photovoltaic power
generation systems depends on the solar irradiation and temperature.
The PV system can supply the maximum power to the load at a
particular operating point which is generally called as maximum
power point (MPP), at which the entire PV system operates with
maximum efficiency and produces its maximum power. Hence, a
Maximum power point tracking (MPPT) methods are used to
maximize the PV array output power by tracking continuously the
maximum power point. The proposed MPPT controller is designed
for 10kW solar PV system installed at Cape Institute of Technology.
This paper presents the fuzzy logic based MPPT algorithm. However,
instead of one type of membership function, different structures of
fuzzy membership functions are used in the FLC design. The
proposed controller is combined with the system and the results are
obtained for each membership functions in Matlab/Simulink
environment. Simulation results are decided that which membership
function is more suitable for this system.
Abstract: Underwater acoustic network is one of the rapidly
growing areas of research and finds different applications for
monitoring and collecting various data for environmental studies. The
communication among dynamic nodes and high error probability in
an acoustic medium forced to maximize energy consumption in
Underwater Sensor Networks (USN) than in traditional sensor
networks. Developing energy-efficient routing protocol is the
fundamental and a curb challenge because all the sensor nodes are
powered by batteries, and they cannot be easily replaced in UWSNs.
This paper surveys the various recent routing techniques that mainly
focus on energy efficiency.
Abstract: This paper focuses on the dynamic behavior of
reinforced concrete (RC) slabs. Therefore, the theoretical modal
analysis was performed using two different types of boundary
conditions. Modal analysis method is the most important dynamic
analyses. The analysis would be modal case when there is no external
force on the structure. By using this method in this paper, the effects
of freely and simply supported boundary conditions on the
frequencies and mode shapes of RC square slabs are studied. ANSYS
software was employed to derive the finite element model to
determine the natural frequencies and mode shapes of the slabs.
Then, the obtained results through numerical analysis (finite element
analysis) would be compared with the exact solution. The main goal
of the research study is to predict how the boundary conditions
change the behavior of the slab structures prior to performing
experimental modal analysis. Based on the results, it is concluded
that simply support boundary condition has obvious influence to
increase the natural frequencies and change the shape of the mode
when it is compared with freely supported boundary condition of
slabs. This means that such support conditions have the direct
influence on the dynamic behavior of the slabs. Thus, it is suggested
to use free-free boundary condition in experimental modal analysis to
precisely reflect the properties of the structure. By using free-free
boundary conditions, the influence of poorly defined supports is
interrupted.
Abstract: This paper presents the hardware implemented and
validation for a special system to assist the unprofessional users of
car with back trailers. The system consists of two platforms; the front
car platform (C) and the trailer platform (T). The main objective is to
control the Trailer platform using the actuators found in the front
platform (c). The mobility of the platform (C) is investigated and
inverse and forward kinematics model is obtained for both platforms
(C) and (T).The system is simulated using Matlab M-file and the
simulation examples results illustrated the system performance. The
system is constructed with a hardware setup for the front and trailer
platform. The hardware experimental results and the simulated
examples outputs showed the validation of the hardware setup.
Abstract: The fuzzy composition of objects depicted in images
acquired through MR imaging or the use of bio-scanners has often
been a point of controversy for field experts attempting to effectively
delineate between the visualized objects. Modern approaches in
medical image segmentation tend to consider fuzziness as a
characteristic and inherent feature of the depicted object, instead of
an undesirable trait. In this paper, a novel technique for efficient
image retrieval in the context of images in which segmented objects
are either crisp or fuzzily bounded is presented. Moreover, the
proposed method is applied in the case of multiple, even conflicting,
segmentations from field experts. Experimental results demonstrate
the efficiency of the suggested method in retrieving similar objects
from the aforementioned categories while taking into account the
fuzzy nature of the depicted data.
Abstract: The research conducted in early seventies apparently
assumed the existence of a universal decision model for union
negotiators and furthermore tended to regard financial information as
a ‘neutral’ input into a rational decision making process. However,
research in the eighties began to question the neutrality of financial
information as an input in collective bargaining rather viewing it as a
potentially effective means for controlling the labour force.
Furthermore, this later research also started challenging the simplistic
assumptions relating particularly to union objectives which have
underpinned the earlier search for universal union decision models.
Despite the above developments there seems to be a dearth of studies
in developing countries concerning the use of financial information in
collective bargaining. This paper seeks to begin to remedy this
deficiency. Utilising a case study approach based on two enterprises,
one in the public sector and the other a multinational, the universal
decision model is rejected and it is argued that the decision whether
or not to use financial information is a contingent one and such a
contingency is largely defined by the context and environment in
which both union and management negotiators work. An attempt is
also made to identify the factors constraining as well as promoting
the use of financial information in collective bargaining, these being
regarded as unique to the organisations within which the case studies
are conducted.
Abstract: E-business technologies, whereby business
transactions are conducted remotely using the Internet, present
unique opportunities and challenges for business. E-business
technologies are applicable to a wide range of organizations and
small and medium-sized enterprises (SMEs) are no exception. There
is an established body of literature about e-business, looking at
definitions, concepts, benefits and challenges. In general, however,
the research focus has been on larger organizations, not SMEs. In an
attempt to redress the balance of research, this paper looks at ebusiness
technologies specifically from a small business perspective.
It seeks to identify the possible barriers that SMEs might face when
considering adoption of the e-business concept and practice as part of
their business process change initiatives and implementation. To
facilitate analysis of these barriers a conceptual framework has been
developed which outlines the key conceptual and practical challenges
of e-business implementation in SMEs. This is developed following a
literature survey comprised of three categories: characteristics of
SMEs, issues of IS/IT use in SMEs and general e-business adoption
and implementation issues. The framework is then empirically
assessed against 7 SMEs who have yet to implement e-business or
whose e-business efforts have been unsatisfactory. Conclusions from
the case studies can be used to verify the framework, and set
parameters for further larger scale empirical investigation.
Abstract: Enterprise Architecture (EA) is a strategy that is
employed by enterprises in order to align their business and
Information Technology (IT). EA is managed, developed, and
maintained through Enterprise Architecture Implementation
Methodology (EAIM). Effectiveness of EA implementation is the
degree in which EA helps to achieve the collective goals of the
organization. This paper analyzes the results of a survey that aims to
explore the factors that affect the effectiveness of EAIM and
specifically the relationship between factors and effectiveness of the
output and functionality of EA project. The exploratory factor
analysis highlights a specific set of five factors: alignment,
adaptiveness, support, binding, and innovation. The regression
analysis shows that there is a statistically significant and positive
relationship between each of the five factors and the effectiveness of
EAIM. Consistent with theory and practice, the most prominent
factor for developing an effective EAIM is innovation. The findings
contribute to the measuring the effectiveness of EA implementation
project by providing an indication of the measurement
implementation approaches which is used by the Enterprise
Architects, and developing an effective EAIM.
Abstract: Images are important source of information used as
evidence during any investigation process. Their clarity and accuracy
is essential and of the utmost importance for any investigation.
Images are vulnerable to losing blocks and having noise added to
them either after alteration or when the image was taken initially,
therefore, having a high performance image processing system and it
is implementation is very important in a forensic point of view. This
paper focuses on improving the quality of the forensic images.
For different reasons packets that store data can be affected,
harmed or even lost because of noise. For example, sending the
image through a wireless channel can cause loss of bits. These types
of errors might give difficulties generally for the visual display
quality of the forensic images.
Two of the images problems: noise and losing blocks are covered.
However, information which gets transmitted through any way of
communication may suffer alteration from its original state or even
lose important data due to the channel noise. Therefore, a developed
system is introduced to improve the quality and clarity of the forensic
images.
Abstract: Mobile social games recently become extremely
popular, spawning a whole new entertainment culture. However,
mobile game players are fickle, quickly and easily picking up and
abandoning games. This pilot study seeks to identify factors that
influence users to discontinuing playing mobile social games. We
identified three sacrifices which can prompt users to abandon games:
monetary sacrifice, time sacrifice and privacy sacrifice. The results
showed that monetary sacrifice has a greater impact than the other two
factors in causing players to discontinue usage intention.
Abstract: The dramatic rise in the use of Social Media (SM)
platforms such as Facebook and Twitter provide access to an
unprecedented amount of user data. Users may post reviews on
products and services they bought, write about their interests, share
ideas or give their opinions and views on political issues. There is a
growing interest in the analysis of SM data from organisations for
detecting new trends, obtaining user opinions on their products and
services or finding out about their online reputations. A recent
research trend in SM analysis is making predictions based on
sentiment analysis of SM. Often indicators of historic SM data are
represented as time series and correlated with a variety of real world
phenomena like the outcome of elections, the development of
financial indicators, box office revenue and disease outbreaks. This
paper examines the current state of research in the area of SM mining
and predictive analysis and gives an overview of the analysis
methods using opinion mining and machine learning techniques.
Abstract: As enterprise computing becomes more and more
complex, the costs and technical challenges of IT system maintenance
and support are increasing rapidly. One popular approach to managing
IT system maintenance is to prepare and use a FAQ (Frequently Asked
Questions) system to manage and reuse systems knowledge. Such a
FAQ system can help reduce the resolution time for each service
incident ticket. However, there is a major problem where over time the
knowledge in such FAQs tends to become outdated. Much of the
knowledge captured in the FAQ requires periodic updates in response
to new insights or new trends in the problems addressed in order to
maintain its usefulness for problem resolution. These updates require a
systematic approach to define the exact portion of the FAQ and its
content. Therefore, we are working on a novel method to
hierarchically structure the FAQ and automate the updates of its
structure and content. We use structured information and the
unstructured text information with the timelines of the information in
the service incident tickets. We cluster the tickets by structured
category information, by keywords, and by keyword modifiers for the
unstructured text information. We also calculate an urgency score
based on trends, resolution times, and priorities. We carefully studied
the tickets of one of our projects over a 2.5-year time period. After the
first 6 months we started to create FAQs and confirmed they improved
the resolution times. We continued observing over the next 2 years to
assess the ongoing effectiveness of our method for the automatic FAQ
updates. We improved the ratio of tickets covered by the FAQ from
32.3% to 68.9% during this time. Also, the average time reduction of
ticket resolution was between 31.6% and 43.9%. Subjective analysis
showed more than 75% reported that the FAQ system was useful in
reducing ticket resolution times.
Abstract: A key issue in seismic risk analysis within the context
of Performance-Based Earthquake Engineering is the evaluation of
the expected seismic damage of structures under a specific
earthquake ground motion. The assessment of the seismic
performance strongly depends on the choice of the seismic Intensity
Measure (IM), which quantifies the characteristics of a ground
motion that are important to the nonlinear structural response. Several
conventional IMs of ground motion have been used to estimate their
damage potential to structures. Yet, none of them has been proved to
be able to predict adequately the seismic damage. Therefore,
alternative, scalar intensity measures, which take into account not
only ground motion characteristics but also structural information
have been proposed. Some of these IMs are based on integration of
spectral values over a range of periods, in an attempt to account for
the information that the shape of the acceleration, velocity or
displacement spectrum provides. The adequacy of a number of these
IMs in predicting the structural damage of 3D R/C buildings is
investigated in the present paper. The investigated IMs, some of
which are structure specific and some are non structure-specific, are
defined via integration of spectral values. To achieve this purpose
three symmetric in plan R/C buildings are studied. The buildings are
subjected to 59 bidirectional earthquake ground motions. The two
horizontal accelerograms of each ground motion are applied along
the structural axes. The response is determined by nonlinear time
history analysis. The structural damage is expressed in terms of the
maximum interstory drift as well as the overall structural damage
index. The values of the aforementioned seismic damage measures
are correlated with seven scalar ground motion IMs. The comparative
assessment of the results revealed that the structure-specific IMs
present higher correlation with the seismic damage of the three
buildings. However, the adequacy of the IMs for estimation of the
structural damage depends on the response parameter adopted.
Furthermore, it was confirmed that the widely used spectral
acceleration at the fundamental period of the structure is a good
indicator of the expected earthquake damage level.
Abstract: Tumor is an uncontrolled growth of tissues in any part
of the body. Tumors are of different types and they have different
characteristics and treatments. Brain tumor is inherently serious and
life-threatening because of its character in the limited space of the
intracranial cavity (space formed inside the skull). Locating the tumor
within MR (magnetic resonance) image of brain is integral part of the
treatment of brain tumor. This segmentation task requires
classification of each voxel as either tumor or non-tumor, based on
the description of the voxel under consideration. Many studies are
going on in the medical field using Markov Random Fields (MRF) in
segmentation of MR images. Even though the segmentation process
is better, computing the probability and estimation of parameters is
difficult. In order to overcome the aforementioned issues, Conditional
Random Field (CRF) is used in this paper for segmentation, along
with the modified artificial bee colony optimization and modified
fuzzy possibility c-means (MFPCM) algorithm. This work is mainly
focused to reduce the computational complexities, which are found in
existing methods and aimed at getting higher accuracy. The
efficiency of this work is evaluated using the parameters such as
region non-uniformity, correlation and computation time. The
experimental results are compared with the existing methods such as
MRF with improved Genetic Algorithm (GA) and MRF-Artificial
Bee Colony (MRF-ABC) algorithm.
Abstract: In oases, the surface water resources are becoming
increasingly scarce and groundwater resources, which generally have
a poor quality due to the high levels of salinity, are often
overexploited. Water saving have therefore become imperative for
better oases sustainability. If drip irrigation is currently recommended
in Morocco for saving water and valuing, its use in the sub-desert
areas does not keep water safe from high evaporation rates. An
alternative to this system would be the use of subsurface drip
irrigation. This technique is defined as an application of water under
the soil surface through drippers, which deliver water at rates
generally similar to surface drip irrigation. As subsurface drip
irrigation is a recently introduced in Morocco, a better understanding
of the infiltration process around a buried source, in local conditions,
and its impact on plant growth is necessarily required. This study
aims to contribute to improving the water use efficiency by testing
the performance of subsurface irrigation system, especially in areas
where water is a limited source. The objectives of this research are
performance evaluation in arid conditions of the subsurface drip
irrigation system for young date palms compared to the surface drip.
In this context, an experimental test is installed at a farmer’s field in
the area of Erfoud (Errachidia Province, southeastern Morocco),
using the subsurface drip irrigation system in comparison with the
classic drip system for young date palms. Flow measurement to
calculate the uniformity of the application of water was done through
two methods: a flow measurement of drippers above the surface and
another one underground. The latter method has also helped us to
estimate losses through evaporation for both irrigation techniques. In
order to compare the effect of two irrigation modes, plants were
identified for each type of irrigation to monitor certain agronomic
parameters (cumulative numbers of palms and roots development).
Experimentation referred to a distribution uniformity of about 88%;
considered acceptable for subsurface drip irrigation while it is around
80% for the surface drip irrigation. The results also show an increase
in root development and in the number of palm, as well as a
substantial water savings due to lower evaporation losses compared
to the classic drip irrigation.
The results of this study showed that subsurface drip irrigation is
an efficient technique, which allows sustainable irrigation in arid
areas.