Abstract: The objective of this paper, is to apply support vector machine (SVM) approach for the classification of cancerous and normal regions of prostate images. Three kinds of textural features are extracted and used for the analysis: parameters of the Gauss- Markov random field (GMRF), correlation function and relative entropy. Prostate images are acquired by the system consisting of a microscope, video camera and a digitizing board. Cross-validated classification over a database of 46 images is implemented to evaluate the performance. In SVM classification, sensitivity and specificity of 96.2% and 97.0% are achieved for the 32x32 pixel block sized data, respectively, with an overall accuracy of 96.6%. Classification performance is compared with artificial neural network and k-nearest neighbor classifiers. Experimental results demonstrate that the SVM approach gives the best performance.
Abstract: This paper describes an experience of research,
development and innovation applied in Industrial Naval at (Science
and Technology Corporation for the Development of Shipbuilding
Industry, Naval in Colombia (COTECMAR) particularly through
processes of research, innovation and technological development,
based on theoretical models related to organizational knowledge
management, technology management and management of human
talent and integration of technology platforms. It seeks ways to
facilitate the initial establishment of environments rich in
information, knowledge and content-supported collaborative
strategies on dynamic processes missionary, seeking further
development in the context of research, development and innovation
of the Naval Engineering in Colombia, making it a distinct basis for
the generation of knowledge assets from COTECMAR.
The integration of information and communication technologies,
supported on emerging technologies (mobile technologies, wireless,
digital content via PDA, and content delivery services on the Web 2.0
and Web 3.0) as a view of the strategic thrusts in any organization
facilitates the redefinition of processes for managing information and
knowledge, enabling the redesign of workflows, the adaptation of
new forms of organization - preferably in networking and support the
creation of symbolic-inside-knowledge promotes the development of
new skills, knowledge and attitudes of the knowledge worker
Abstract: Municipal solid waste (MSW) comprises of a wide
range of heterogeneous materials generated by individual, household
or organization and may include food waste, garden wastes, papers,
textiles, rubbers, plastics, glass, ceramics, metals, wood wastes,
construction wastes but it is not limited to the above mentioned
fractions. The most common Municipal Solid Waste pretreatment
method in use is thermal pretreatment (incineration) and Mechanical
Biological pretreatment. This paper presents an overview of these
two pretreatment methods describing their benefits and laboratory
scale reactors that simulate landfill conditions were constructed in
order to compare emissions in terms of biogas production and
leachate contamination between untreated Municipal Solid Waste and
Mechanical Biological Pretreated waste. The findings of this study
showed that Mechanical Biological pretreatment of waste reduces the
emission level of waste and the benefit over the landfilling of
untreated waste is significant.
Abstract: A spatial classification technique incorporating a State of Art Feature Extraction algorithm is proposed in this paper for classifying a heterogeneous classes present in hyper spectral images. The classification accuracy can be improved if and only if both the feature extraction and classifier selection are proper. As the classes in the hyper spectral images are assumed to have different textures, textural classification is entertained. Run Length feature extraction is entailed along with the Principal Components and Independent Components. A Hyperspectral Image of Indiana Site taken by AVIRIS is inducted for the experiment. Among the original 220 bands, a subset of 120 bands is selected. Gray Level Run Length Matrix (GLRLM) is calculated for the selected forty bands. From GLRLMs the Run Length features for individual pixels are calculated. The Principle Components are calculated for other forty bands. Independent Components are calculated for next forty bands. As Principal & Independent Components have the ability to represent the textural content of pixels, they are treated as features. The summation of Run Length features, Principal Components, and Independent Components forms the Combined Features which are used for classification. SVM with Binary Hierarchical Tree is used to classify the hyper spectral image. Results are validated with ground truth and accuracies are calculated.
Abstract: The only relevant basis for the design of an educational application are objectives of learning for the content area. This study analyses the process in which the real – not only the formal – objectives could work as the starting point for the construction of an educational game. The application context is the education of perioperative nursing. The process is based on the panel discussions of nursing teachers. In the panels, the teachers elaborated the objectives. The transcribed discussions were analysed in terms of the conceptions of learning and teaching of perioperative nursing. The outcome of the study is first the elaborated objectives, which will be used in the implementation of an educational game for the needs of pre-, intra and post-operative nursing skills learning. Second, the study shows that different views of learning are necessary to be understood in order to design an appropriate educational application.
Abstract: The acoustic and articulatory properties of fricative speech sounds are being studied using magnetic resonance imaging (MRI) and acoustic recordings from a single subject. Area functions were derived from a complete set of axial and coronal MR slices using two different methods: the Mermelstein technique and the Blum transform. Area functions derived from the two techniques were shown to differ significantly in some cases. Such differences will lead to different acoustic predictions and it is important to know which is the more accurate. The vocal tract acoustic transfer function (VTTF) was derived from these area functions for each fricative and compared with measured speech signals for the same fricative and same subject. The VTTFs for /f/ in two vowel contexts and the corresponding acoustic spectra are derived here; the Blum transform appears to show a better match between prediction and measurement than the Mermelstein technique.
Abstract: Key management is a vital component in any modern security protocol. Due to scalability and practical implementation considerations automatic key management seems a natural choice in significantly large virtual private networks (VPNs). In this context IETF Internet Key Exchange (IKE) is the most promising protocol under permanent review. We have made a humble effort to pinpoint IKEv2 net gain over IKEv1 due to recent modifications in its original structure, along with a brief overview of salient improvements between the two versions. We have used US National Institute of Technology NIIST VPN simulator to get some comparisons of important performance metrics.
Abstract: Grid computing provides a virtual framework for
controlled sharing of resources across institutional boundaries.
Recently, trust has been recognised as an important factor for
selection of optimal resources in a grid. We introduce a new method
that provides a quantitative trust value, based on the past interactions
and present environment characteristics. This quantitative trust value
is used to select a suitable resource for a job and eliminates run time
failures arising from incompatible user-resource pairs. The proposed
work will act as a tool to calculate the trust values of the various
components of the grid and there by improves the success rate of the
jobs submitted to the resource on the grid. The access to a resource
not only depend on the identity and behaviour of the resource but
also upon its context of transaction, time of transaction, connectivity
bandwidth, availability of the resource and load on the resource. The
quality of the recommender is also evaluated based on the accuracy
of the feedback provided about a resource. The jobs are submitted for
execution to the selected resource after finding the overall trust value
of the resource. The overall trust value is computed with respect to
the subjective and objective parameters.
Abstract: This essay endeavors to read Ama Ata Aidoo-s Our Sister Killjoy with a postocolonially-inflected consciousness. It aims at demonstrating how her work could be read as a sophisticated postcolonial revision of the colonial travel narrative whereby the protagonist-s black-eyed squint operates as 'the all-seeing-eye' to subvert the historically unbroken legacy of the Orientalist ideology. It tries to demonstrate how Sissie assumes authority and voice in an act that destabilizes the traditionally established modes of western representation. It is also an investigation into how Aidoo-s text adopts processes which disengage the Eurocentric view produced by the discursive itineraries of western institutions through diverse acts of resistance and 'various strategies of subversion and appropriation'. Her counter discursive strategies of resistance are shaped up in various ways by a feminist consciousness that attempts to articulate a distinct African version of identity and preserve cultural distinctiveness.
Abstract: Since dealing with high dimensional data is
computationally complex and sometimes even intractable, recently
several feature reductions methods have been developed to reduce
the dimensionality of the data in order to simplify the calculation
analysis in various applications such as text categorization, signal
processing, image retrieval, gene expressions and etc. Among feature
reduction techniques, feature selection is one the most popular
methods due to the preservation of the original features.
In this paper, we propose a new unsupervised feature selection
method which will remove redundant features from the original
feature space by the use of probability density functions of various
features. To show the effectiveness of the proposed method, popular
feature selection methods have been implemented and compared.
Experimental results on the several datasets derived from UCI
repository database, illustrate the effectiveness of our proposed
methods in comparison with the other compared methods in terms of
both classification accuracy and the number of selected features.
Abstract: This paper presents an approach for repairing word order errors in English text by reordering words in a sentence and choosing the version that maximizes the number of trigram hits according to a language model. A possible way for reordering the words is to use all the permutations. The problem is that for a sentence with length N words the number of all permutations is N!. The novelty of this method concerns the use of an efficient confusion matrix technique for reordering the words. The confusion matrix technique has been designed in order to reduce the search space among permuted sentences. The limitation of search space is succeeded using the statistical inference of N-grams. The results of this technique are very interesting and prove that the number of permuted sentences can be reduced by 98,16%. For experimental purposes a test set of TOEFL sentences was used and the results show that more than 95% can be repaired using the proposed method.
Abstract: This paper presents a novel approach to assessing textile porosity by the application of the image analysis techniques. The images of different types of sample fabrics, taken through a microscope when the fabric is placed over a constant light source,transfer the problem into the image analysis domain. Indeed, porosity can thus be expressed in terms of a brightness percentage index calculated on the digital microscope image. Furthermore, it is meaningful to compare the brightness percentage index with the air permeability and the tightness indices of each fabric type. We have experimentally shown that there exists an approximately linear relation between brightness percentage and air permeability indices.
Abstract: B2E portals represent a new class of web-based
information technologies which many organisations are introducing
in recent years to stay in touch with their distributed workforces and
enable them to perform value added activities for organisations.
However, actual usage of these emerging systems (measured using
suitable instruments) has not been reported in the contemporary
scholarly literature. We argue that many of the instruments to
measure usage of various types of IT-enabled information systems
are not directly applicable for B2E portals because they were
developed for the context of traditional mainframe and PC-based
information systems. It is therefore important to develop a new
instrument for web-based portal technologies aimed at employees. In
this article, we report on the development and initial qualitative
evaluation of an instrument that seeks to operationaise a set of
independent factors affecting the usage of portals by employees. The
proposed instrument is useful to IT/e-commerce researchers and
practitioners alike as it enhances their confidence in predicting
employee usage of portals in organisations.
Abstract: In this paper we present the deep study about the Bio-
Medical Images and tag it with some basic extracting features (e.g.
color, pixel value etc). The classification is done by using a nearest
neighbor classifier with various distance measures as well as the
automatic combination of classifier results. This process selects a
subset of relevant features from a group of features of the image. It
also helps to acquire better understanding about the image by
describing which the important features are. The accuracy can be
improved by increasing the number of features selected. Various
types of classifications were evolved for the medical images like
Support Vector Machine (SVM) which is used for classifying the
Bacterial types. Ant Colony Optimization method is used for optimal
results. It has high approximation capability and much faster
convergence, Texture feature extraction method based on Gabor
wavelets etc..
Abstract: Clusters of microcalcifications in mammograms are an
important sign of breast cancer. This paper presents a complete
Computer Aided Detection (CAD) scheme for automatic detection of
clustered microcalcifications in digital mammograms. The proposed
system, MammoScan μCaD, consists of three main steps. Firstly
all potential microcalcifications are detected using a a method for
feature extraction, VarMet, and adaptive thresholding. This will also
give a number of false detections. The goal of the second step,
Classifier level 1, is to remove everything but microcalcifications.
The last step, Classifier level 2, uses learned dictionaries and sparse
representations as a texture classification technique to distinguish
single, benign microcalcifications from clustered microcalcifications,
in addition to remove some remaining false detections. The system
is trained and tested on true digital data from Stavanger University
Hospital, and the results are evaluated by radiologists. The overall
results are promising, with a sensitivity > 90 % and a low false
detection rate (approx 1 unwanted pr. image, or 0.3 false pr. image).
Abstract: Our adaptive multimodal system aims at correctly
presenting a mathematical expression to visually impaired users.
Given an interaction context (i.e. combination of user, environment
and system resources) as well as the complexity of the expression
itself and the user-s preferences, the suitability scores of different
presentation format are calculated. Unlike the current state-of-the art
solutions, our approach takes into account the user-s situation and not
imposes a solution that is not suitable to his context and capacity. In
this wok, we present our methodology for calculating the
mathematical expression complexity and the results of our
experiment. Finally, this paper discusses the concepts and principles
applied on our system as well as their validation through cases
studies. This work is our original contribution to an ongoing research
to make informatics more accessible to handicapped users.
Abstract: Master plan is a tool to guide and manage the growth of cities in a planned manner. The soul of a master plan lies in its implementation framework. If not implemented, people are trapped in a mess of urban problems and laissez-faire development having serious long term repercussions. Unfortunately, Master Plans prepared for several major cities of Pakistan could not be fully implemented due to host of reasons and Lahore is no exception. Being the second largest city of Pakistan with a population of over 7 million people, Lahore holds the distinction that the first ever Master Plan in the country was prepared for this city in 1966. Recently in 2004, a new plan titled `Integrated Master Plan for Lahore-2021- has been approved for implementation. This paper provides a comprehensive account of the weaknesses and constraints in the plan preparation process and implementation strategies of Master Plans prepared for Lahore. It also critically reviews the new Master Plan particularly with respect to the proposed implementation framework. The paper discusses the prospects and pre-conditions for successful implementation of the new Plan in the light of historic analysis, interviews with stakeholders and the new institutional context under the devolution plan.
Abstract: This paper proposes to use ETM+ multispectral data
and panchromatic band as well as texture features derived from the
panchromatic band for land cover classification. Four texture features
including one 'internal texture' and three GLCM based textures
namely correlation, entropy, and inverse different moment were used
in combination with ETM+ multispectral data. Two data sets
involving combination of multispectral, panchromatic band and its
texture were used and results were compared with those obtained by
using multispectral data alone. A decision tree classifier with and
without boosting were used to classify different datasets. Results
from this study suggest that the dataset consisting of panchromatic
band, four of its texture features and multispectral data was able to
increase the classification accuracy by about 2%. In comparison, a
boosted decision tree was able to increase the classification accuracy
by about 3% with the same dataset.
Abstract: The most influential programming paradigm today
is object oriented (OO) programming and it is widely used in
education and industry. Recognizing the importance of equipping
students with OO knowledge and skills, it is not surprising that most
Computer Science degree programs offer OO-related courses. How
do we assess whether the students have acquired the right objectoriented
skills after they have completed their OO courses? What are
object oriented skills? Currently none of the current assessment
techniques would be able to provide this answer. Traditional forms of
OO programming assessment provide a ways for assigning numerical
scores to determine letter grades. But this rarely reveals information
about how students actually understand OO concept. It appears
reasonable that a better understanding of how to define and assess
OO skills is needed by developing a criterion referenced model. It is
even critical in the context of Malaysia where there is currently a
growing concern over the level of competency of Malaysian IT
graduates in object oriented programming. This paper discussed the
approach used to develop the criterion-referenced assessment model.
The model can serve as a guideline when conducting OO
programming assessment as mentioned. The proposed model is
derived by using Goal Questions Metrics methodology, which helps
formulate the metrics of interest. It concluded with a few suggestions
for further study.
Abstract: Due to dynamic evolution, the ability of a
manufacturing technology to produce a special product is changing.
Therefore, it is essential to monitor the established techniques and
processes to detect whether a company-s production will fit future
circumstances. Concerning the manufacturing technology planning
process, companies must decide when to change to a new technology
for maintaining and increasing competitive advantages. In this
context, the maturity assessment of the focused technologies is
crucial. This article presents an approach for defining the maturity of
a manufacturing technology from a strategic point of view. The
concept is based on the approach of technology readiness level
(TRL) according to NASA (National Aeronautics and Space
Administration), but also includes dynamic changes. Therefore, the
model takes into account the concept of the technology life cycle.
Furthermore, it enables a company to estimate the ideal date for
implementation of a new manufacturing technology.