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: In this paper, the formulation of a new group explicit
method with a fourth order accuracy is described in solving the two
dimensional Helmholtz equation. The formulation is based on the
nine-point fourth order compact finite difference approximation
formula. The complexity analysis of the developed scheme is also
presented. Several numerical experiments were conducted to test the
feasibility of the developed scheme. Comparisons with other existing
schemes will be reported and discussed. Preliminary results indicate
that this method is a viable alternative high accuracy solver to the
Helmholtz equation.
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: Accounting policies are a set of solutions compliant
with legal regulations that an entity selects and adopts, and which
guarantee a proper quality of financial statements. Those solutions
may differ depending on whether the entity adopts national or
international accounting standards.
The aim of this article is to present accounting principles (policies)
in Polish and international legal regulations and their adoption in
selected Polish companies listed on the Warsaw Stock Exchange. The
research method adopted in this work is the analysis and evaluation
of legal conditions in Polish companies.
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: In this paper, Least Mean Square (LMS) adaptive
noise reduction algorithm is proposed to enhance the speech signal
from the noisy speech. In this, the speech signal is enhanced by
varying the step size as the function of the input signal. Objective and
subjective measures are made under various noises for the proposed
and existing algorithms. From the experimental results, it is seen that
the proposed LMS adaptive noise reduction algorithm reduces Mean
square Error (MSE) and Log Spectral Distance (LSD) as compared to
that of the earlier methods under various noise conditions with
different input SNR levels. In addition, the proposed algorithm
increases the Peak Signal to Noise Ratio (PSNR) and Segmental SNR
improvement (ΔSNRseg) values; improves the Mean Opinion Score
(MOS) as compared to that of the various existing LMS adaptive
noise reduction algorithms. From these experimental results, it is
observed that the proposed LMS adaptive noise reduction algorithm
reduces the speech distortion and residual noise as compared to that
of the existing methods.
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: An active slat is developed to increase the lift and delay
the separation for a DU96-W180 airfoil. The active slat is a fixed slat
that can be closed, fully opened or intermittently opened by a rotating
vane depending on the need. Experimental results show that the active
slat has reduced the mean pressure and increased the mean velocity
on the suction side of the airfoil for all positive angles of attack,
indicating an increase of lift. The experimental data and numerical
simulations also show that the direction of actuator vane rotation can
influence the mixing of the flow streams on the suction side and
hence influence the aerodynamic performance.
Abstract: A cleaner production project was implemented in a
bakery. The project is based on the substitution of the best available
technique for an obsolete leaven production technology. The new
technology enables production of durable, high-quality leavens.
Moreover, 25% of flour as the original raw material can be replaced
by pastry from the previous day production which has not been sold.
That pastry was previously disposed in a waste incineration plant.
Besides the environmental benefits resulting from less waste, lower
consumption of energy, reduction of sewage waters quantity and
floury dustiness there are also significant economic benefits. Payback
period of investment was calculated with help of static method of
financial analysis about 2.6 years, using dynamic method 3.5 years
and an internal rate of return more than 29%. The supposed annual
average profit after taxationin the second year of operation was
incompliance with the real profit.
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: 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: In the UK, flooding is responsible for significant
losses to the economy due to the impact on businesses, the vast
majority of which are Small and Medium Enterprises (SMEs).
Businesses of this nature tend to lack formal plans to aid their
response to and recovery from disruptive events such as flooding.
This paper reports on work on how an agent-based model (ABM) is
being developed based on interview data gathered from SMEs at-risk
of flooding and/or have direct experience of flooding. The ABM will
enable simulations to be performed allowing investigations of
different response strategies which SMEs may employ to lessen the
impact of flooding, thus strengthening their resilience.
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: The present study was conducted to evaluate the
potential applicability of biological trickling filter system for the
treatment of simulated textile wastewater containing reactive azo
dyes with bacterial consortium under non-sterile conditions. The
percentage decolorization for the treatment of wastewater containing
structurally different dyes was found to be higher than 95% in all
trials. The stable bacterial count of the biofilm on stone media of the
trickling filter during the treatment confirmed the presence,
proliferation, dominance and involvement of the added microbial
consortium in the treatment of textile wastewater. Results of
physicochemical parameters revealed the reduction in chemical
oxygen demand (58.5-75.1%), sulphates (18.9-36.5%), and
phosphates (63.6-73.0%). UV-Visible and FTIR spectroscopy
confirmed decolorization of dye containing wastewater was ultimate
consequence of biodegradation. Toxicological studies revealed the
nontoxic nature of degradative metabolites.
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.
Abstract: Oases are complex and fragile agro-ecosystems. They
have always existed in environments characterized by an arid climate,
scarcity of rainfall, high temperatures and high evaporation. These
palms have grown up despite the severity of the physical
characteristics thanks to the water's existence and irrigation practice.
The oases are generally spread along non-perennial rivers (wadis),
shallow water table or deep artesian groundwater. However, the
sustainability of oasis system is threatened by water scarcity and
declining of water table levels particularly in arid areas. Located in
the southern east area of Morocco, Tafilalet plain encompasses one of
the largest palm groves in the kingdom. In recent years, this area has
become increasingly threatened by water shortage and has seen a
sharp deterioration under the effect of several combined
anthropogenic and climatic factors. The Bayoud disease, successive
years of drought, Hassan Addakhil dam construction etc are all
factors that have affected both water and phoenicicole heritage of the
area. The objective of this study is to understand the interaction
between qualitative and quantitative degradation of groundwater
resources, and the palm grove dynamics, while reviewing the
assumption that groundwater resources contribute in a direct way to
the conservation of this oasis agroecosystem. A historical analysis
tracing both the oasis dynamics and the groundwater evolution has
been established. Data were collected from satellite images, surveys
with different actors (farmers, Regional Office for Agricultural
Development, Basin agency...). They were complemented by a
synthesis of numerous technical reports in the area. The results
showed that within 40 years, the thickness of the groundwater table
has dropped in 50 %. Along with this, there has been a downsizing of
date palm by 50 %. Areas with higher groundwater level were the
least affected by the downsizing. So we can say that the shallow
groundwater contribute significantly and directly to the water supply
of date palm through its root system, and largely ensures the oasis
ecosystem sustainability.