Abstract: Image spam is a kind of email spam where the spam
text is embedded with an image. It is a new spamming technique
being used by spammers to send their messages to bulk of internet
users. Spam email has become a big problem in the lives of internet
users, causing time consumption and economic losses. The main
objective of this paper is to detect the image spam by using histogram
properties of an image. Though there are many techniques to
automatically detect and avoid this problem, spammers employing
new tricks to bypass those techniques, as a result those techniques are
inefficient to detect the spam mails. In this paper we have proposed a
new method to detect the image spam. Here the image features are
extracted by using RGB histogram, HSV histogram and combination
of both RGB and HSV histogram. Based on the optimized image
feature set classification is done by using k- Nearest Neighbor(k-NN)
algorithm. Experimental result shows that our method has achieved
better accuracy. From the result it is known that combination of RGB
and HSV histogram with k-NN algorithm gives the best accuracy in
spam detection.
Abstract: Steganography is the art and science that hides the information in an appropriate cover carrier like image, text, audio and video media. In this work the authors propose a new image based steganographic method for hiding information within the complex bit planes of the image. After slicing into bit planes the cover image is analyzed to extract the most complex planes in decreasing order based on their bit plane complexity. The complexity function next determines the complex noisy blocks of the chosen bit plane and finally pixel mapping method (PMM) has been used to embed secret bits into those regions of the bit plane. The novel approach of using pixel mapping method (PMM) in bit plane domain adaptively embeds data on most complex regions of image, provides high embedding capacity, better imperceptibility and resistance to steganalysis attack.
Abstract: The growth in the volume of text data such as books
and articles in libraries for centuries has imposed to establish
effective mechanisms to locate them. Early techniques such as
abstraction, indexing and the use of classification categories have
marked the birth of a new field of research called "Information
Retrieval". Information Retrieval (IR) can be defined as the task of
defining models and systems whose purpose is to facilitate access to
a set of documents in electronic form (corpus) to allow a user to find
the relevant ones for him, that is to say, the contents which matches
with the information needs of the user.
Most of the models of information retrieval use a specific data
structure to index a corpus which is called "inverted file" or "reverse
index".
This inverted file collects information on all terms over the corpus
documents specifying the identifiers of documents that contain the
term in question, the frequency of each term in the documents of the
corpus, the positions of the occurrences of the word...
In this paper we use an oriented object database (db4o) instead of
the inverted file, that is to say, instead to search a term in the inverted
file, we will search it in the db4o database.
The purpose of this work is to make a comparative study to see if
the oriented object databases may be competing for the inverse index
in terms of access speed and resource consumption using a large
volume of data.
Abstract: In this paper, Fuzzy C-Means clustering with
Expectation Maximization-Gaussian Mixture Model based hybrid
modeling algorithm is proposed for Continuous Tamil Speech
Recognition. The speech sentences from various speakers are used
for training and testing phase and objective measures are between the
proposed and existing Continuous Speech Recognition algorithms.
From the simulated results, it is observed that the proposed algorithm
improves the recognition accuracy and F-measure up to 3% as
compared to that of the existing algorithms for the speech signal from
various speakers. In addition, it reduces the Word Error Rate, Error
Rate and Error up to 4% as compared to that of the existing
algorithms. In all aspects, the proposed hybrid modeling for Tamil
speech recognition provides the significant improvements for speechto-
text conversion in various applications.
Abstract: Communicating and managing customers’
requirements in software development projects play a vital role in the
software development process. While it is difficult to do so locally, it
is even more difficult to communicate these requirements over
distributed boundaries and to convey them to multiple distribution
customers. This paper discusses the communication of multiple
distribution customers’ requirements in the context of customised
software products. The main purpose is to understand the challenges
of communicating and managing customisation requirements across
distributed boundaries. We propose a model for Communicating
Customisation Requirements of Multi-Clients in a Distributed
Domain (CCRD). Thereafter, we evaluate that model by presenting
the findings of a case study conducted with a company with
customisation projects for 18 distributed customers. Then, we
compare the outputs of the real case process and the outputs of the
CCRD model using simulation methods. Our conjecture is that the
CCRD model can reduce the challenge of communication
requirements over distributed organisational boundaries, and the
delay in decision making and in the entire customisation process
time.
Abstract: This paper discusses the role of music as a ludic
activity and constituent element of voice in the construction and
consolidation of the relationship of the baby and his/her mother or
caretaker, evaluating its implications in his/her psychic structure and
constitution as a subject. The work was based on the research
developed as part of the author’s doctoral activities carried out from
her insertion in a project of the Music Department of Federal
University of Rio Grande do Sul - UFRGS, which objective was the
development of musical activities with groups of babies from 0 to 24
months old and their caretakers. Observations, video recordings of
the meetings, audio testemonies, and evaluation tools applied to
group participants were used as instruments for this research.
Information was collected on the participation of 195 babies, among
which 8 were more focused on through interviews with their mothers
or caretakers. These interviews were analyzed based on the
referential of French Discourse Analysis, Psychoanalysis, Psychology
of Development and Musical Education. The results of the research
were complemented by other posterior experiences that the author
developed with similar groups, in a context of a private clinic. The
information collected allowed the observation of the ludic and
structural functions of musical activities, when developed in a
structured environment, as well as the importance of the musicality of
the mother’s voice to the psychical structuring of the baby, allowing
his/her insertion in the language and his/her constitution as a subject.
Abstract: Due to the importance of ports to trade and economic
development of the regions in which they are inserted, in recent
decades the number of studies devoted to this subject has increased.
Part of these studies considers the ports as business agglomerations
and focuses on port governance. This is an important approach since
the port performance is the result of activities performed by actors
belonging to the port-logistics chain, which need to be properly
coordinated. This coordination takes place through a port governance
model. Given this context, this study aims to analyze the governance
model of the port of Santos from the perspective of port customers.
To do this, a closed-ended questionnaire based on a conceptual model
that considers the key dimensions associated with port governance
was applied to the international freight forwarders that operate in the
port. The results show the applicability of the considered model and
highlight improvement opportunities to be implemented at the port of
Santos.
Abstract: Urban public spaces are sutured with a range of
surveillance and sensor technologies that claim to enable new forms
of ‘data based citizen participation’, but also increase the tendency
for ‘function-creep’, whereby vast amounts of data are gathered,
stored and analysed in a broad application of urban surveillance. This
kind of monitoring and capacity for surveillance connects with
attempts by civic authorities to regulate, restrict, rebrand and reframe
urban public spaces. A direct consequence of the increasingly
security driven, policed, privatised and surveilled nature of public
space is the exclusion or ‘unfavourable inclusion’ of those considered
flawed and unwelcome in the ‘spectacular’ consumption spaces of
many major urban centres. In the name of urban regeneration,
programs of securitisation, ‘gentrification’ and ‘creative’ and ‘smart’
city initiatives refashion public space as sites of selective inclusion
and exclusion. In this context of monitoring and control procedures,
in particular, children and young people’s use of space in parks,
neighbourhoods, shopping malls and streets is often viewed as a
threat to the social order, requiring various forms of remedial action.
This paper suggests that cities, places and spaces and those who
seek to use them, can be resilient in working to maintain and extend
democratic freedoms and processes enshrined in Marshall’s concept
of citizenship, calling sensor and surveillance systems to account.
Such accountability could better inform the implementation of public
policy around the design, build and governance of public space and
also understandings of urban citizenship in the sensor saturated urban
environment.
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: 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 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: 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: 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: Augmented Reality is a technology that involves the
overlay of virtual content, which is context or environment sensitive,
on images of the physical world in real time. This paper presents the
development of a catalog system that facilitates and allows the
creation, publishing, management and exploitation of augmented
multimedia contents and Augmented Reality applications, creating an
own space for anyone that wants to provide information to real
objects in order to edit and share it then online with others. These
spaces would be built for different domains without the initial need of
expert users. Its operation focuses on the context of Web 2.0 or
Social Web, with its various applications, developing contents to
enrich the real context in which human beings act permitting the
evolution of catalog’s contents in an emerging way.
Abstract: In today’s highly competitive, dynamic and
technology driven business circumstances, marketers are under
steady pressure to deliver the best. Organizations are continuously
improving and upgrading themselves to meet customer expectations
and demands. Technology has not only changed the way in which
business is done in modern times but has also transformed the way to
reach out to target audience. Marketers have identified most recent
media options to communicate and convince potential customers.
Numerous scholars have studied the research domain of advertising
and have tried to recognize different measures of advertisement
effectiveness in context of various media. The objective of this paper
is to critically review accessible literature on advertisement
effectiveness in context of varied advertising media, recognize major
gaps in the literature and identify future research prospects on the
basis of critical analysis of literature.
Abstract: Skin detection is an important task for computer
vision systems. A good method of skin detection means a good and
successful result of the system.
The colour is a good descriptor for image segmentation and
classification; it allows detecting skin colour in the images. The
lighting changes and the objects that have a colour similar than skin
colour make the operation of skin detection difficult.
In this paper, we proposed a method using the YCbCr colour space
for skin detection and lighting effects elimination, then we use the
information of texture to eliminate the false regions detected by the
YCbCr skin model.