Abstract: In Secondary Surveillance Radar (SSR) systems, it is
more difficult to locate and recognise aircrafts in the neighbourhood of civil airports since aerial traffic becomes greater. Here, we propose to apply a recent Blind Source Separation (BSS) algorithm based
on Time-Frequency Analysis, in order to separate messages sent by different aircrafts and falling in the same radar beam in reception. The above source separation method involves joint-diagonalization
of a set of smoothed version of spatial Wigner-Ville distributions.
The technique makes use of the difference in the t-f signatures of the nonstationary sources to be separated. Consequently, as the SSR sources emit different messages at different frequencies, the above fitted to this new application. We applied the technique in simulation to separate SSR replies. Results are provided at the end
of the paper.
Abstract: This paper presents a computational study of the separated flow in a planer asymmetric diffuser. The steady RANS equations for turbulent incompressible fluid flow and six turbulence closures are used in the present study. The commercial software code, FLUENT 6.3.26, was used for solving the set of governing equations using various turbulence models. Five of the used turbulence models are available directly in the code while the v2-f turbulence model was implemented via User Defined Scalars (UDS) and User Defined Functions (UDF). A series of computational analysis is performed to assess the performance of turbulence models at different grid density. The results show that the standard k-ω, SST k-ω and v2-f models clearly performed better than other models when an adverse pressure gradient was present. The RSM model shows an acceptable agreement with the velocity and turbulent kinetic energy profiles but it failed to predict the location of separation and attachment points. The standard k-ε and the low-Re k- ε delivered very poor results.
Abstract: There is a world-wide need for the development of sustainable management strategies to control pest infestation and the development of phosphine (PH3) resistance in lesser grain borer (Rhyzopertha dominica). Computer simulation models can provide a relatively fast, safe and inexpensive way to weigh the merits of various management options. However, the usefulness of simulation models relies on the accurate estimation of important model parameters, such as mortality. Concentration and time of exposure are both important in determining mortality in response to a toxic agent. Recent research indicated the existence of two resistance phenotypes in R. dominica in Australia, weak and strong, and revealed that the presence of resistance alleles at two loci confers strong resistance, thus motivating the construction of a two-locus model of resistance. Experimental data sets on purified pest strains, each corresponding to a single genotype of our two-locus model, were also available. Hence it became possible to explicitly include mortalities of the different genotypes in the model. In this paper we described how we used two generalized linear models (GLM), probit and logistic models, to fit the available experimental data sets. We used a direct algebraic approach generalized inverse matrix technique, rather than the traditional maximum likelihood estimation, to estimate the model parameters. The results show that both probit and logistic models fit the data sets well but the former is much better in terms of small least squares (numerical) errors. Meanwhile, the generalized inverse matrix technique achieved similar accuracy results to those from the maximum likelihood estimation, but is less time consuming and computationally demanding.
Abstract: Culture and family structure provide a sense security.
Further, the chrono, macro and micro contexts of development
influence developmental transitions and timetable particularly owing
to variations in the macrosystem associated with non normative life
events like migration. Migration threatens family links, security and
attachment bonds. Rising migratory trends have prompted an
increased interest in migration consequences on familial bonds,
developmental autonomy, socialization process, and sense of
security. This paper takes a narrative approach and applies the
attachment paradigm from a lifespan perspective, to examine the
settlement experiences of an India-born migrant student in Sydney,
Australia. It focuses on her quest to preserve family ties; her remote
secure base; her continual struggle to balance dependency and
autonomy, a major developmental milestone. As positional parental
power is culturally more potent in the Indian society, the paper
therefore raises some important concerns related to cultural
expectations, adaptation, acculturative stress and sense of security.
Abstract: For a variety of safety and economic reasons, engineering undergraduates in Australia have experienced diminishing access to the real hardware that is typically the embodiment of their theoretical studies. This trend will delay the development of practical competence, decrease the ability to model and design, and suppress motivation. The author has attempted to address this concern by creating a software tool that contains both photographic images of real machinery, and sets of graphical modeling 'tools'. Academics from a range of disciplines can use the software to set tutorial tasks, and incorporate feedback comments for a range of student responses. An evaluation of the software demonstrated that students who had solved modeling problems with the aid of the electronic tutor performed significantly better in formal examinations with similar problems. The 2-D graphical diagnostic routines in the Tutor have the potential to be used in a wider range of problem-solving tasks.
Abstract: Artificial Neural Networks (ANNs) have been used successfully in many scientific, industrial and business domains as a method for extracting knowledge from vast amounts of data. However the use of ANN techniques in the sporting domain has been limited. In professional sport, data is stored on many aspects of teams, games, training and players. Sporting organisations have begun to realise that there is a wealth of untapped knowledge contained in the data and there is great interest in techniques to utilise this data. This study will use player data from the elite Australian Football League (AFL) competition to train and test ANNs with the aim to predict the onset of injuries. The results demonstrate that an accuracy of 82.9% was achieved by the ANNs’ predictions across all examples with 94.5% of all injuries correctly predicted. These initial findings suggest that ANNs may have the potential to assist sporting clubs in the prediction of injuries.
Abstract: This paper presents an integrated case based and rule
based reasoning method for car faulty diagnosis. The reasoning
method is done through extracting the past cases from the Proton
Service Center while comparing with the preset rules to deduce a
diagnosis/solution to a car service case. New cases will be stored to
the knowledge base. The test cases examples illustrate the
effectiveness of the proposed integrated reasoning. It has proven
accuracy of similar reasoning if carried out by a service advisor from
the service center.
Abstract: In recent years, “Bottom-up Planning Approach" has been widely accepted and expanded from planning theorists. Citizen participation becomes more important in decision-making in informal settlements. Many of previous projects and strategies due to ignorance of citizen participation, have been failed facing with informal settlements and in some cases lead physical expansion of these neighbourhoods. According to recent experiences, the new participatory approach was in somehow successful. This paper focuses on local experiences in Iran. A considerable amount of people live in informal settlements in Iran. With the previous methods, the government could not solve the problems of these settlements. It is time to examine new methods such as empowerment of the local citizens and involve them to solve the current physical, social, and economic problems. The paper aims to address the previous and new strategies facing with informal settlements, the conditions under which citizens could be involved in planning process, limits and potentials of this process, the main actors and issues and finally motivations that are able to promote citizen participation. Documentary studies, observation, interview and questionnaire have been used to achieve the above mentioned objectives. Nearly 80 percent of responder in Saadi Community are ready to participate in regularising their neighbourhoods, if pre-conditions of citizen involvement are being provided. These pre-conditions include kind of problem and its severity, the importance of issue, existence of a short-term solution, etc. Moreover, confirmation of dweller-s ownership can promote the citizen engagement in participatory projects.
Abstract: In this paper a one-dimension Self Organizing Map
algorithm (SOM) to perform feature selection is presented. The
algorithm is based on a first classification of the input dataset on a
similarity space. From this classification for each class a set of
positive and negative features is computed. This set of features is
selected as result of the procedure. The procedure is evaluated on an
in-house dataset from a Knowledge Discovery from Text (KDT)
application and on a set of publicly available datasets used in
international feature selection competitions. These datasets come
from KDT applications, drug discovery as well as other applications.
The knowledge of the correct classification available for the training
and validation datasets is used to optimize the parameters for positive
and negative feature extractions. The process becomes feasible for
large and sparse datasets, as the ones obtained in KDT applications,
by using both compression techniques to store the similarity matrix
and speed up techniques of the Kohonen algorithm that take
advantage of the sparsity of the input matrix. These improvements
make it feasible, by using the grid, the application of the
methodology to massive datasets.
Abstract: Production of biogas from bakery waste was enhanced
by additional bacterial cell. This study was divided into 2 steps. First
step, grease waste from bakery industry-s grease trap was initially
degraded by Pseudomonas aeruginosa. The concentration of byproduct,
especially glycerol, was determined and found that glycerol
concentration increased from 12.83% to 48.10%. Secondary step, 3
biodigesters were set up in 3 different substrates: non-degraded waste
as substrate in first biodigester, degraded waste as substrate in
secondary biodigester, and degraded waste mixed with swine manure
in ratio 1:1 as substrate in third biodigester. The highest
concentration of biogas was found in third biodigester that was
44.33% of methane and 63.71% of carbon dioxide. The lower
concentration at 24.90% of methane and 18.98% of carbon dioxide
was exhibited in secondary biodigester whereas the lowest was found
in non-degraded waste biodigester. It was demonstrated that the
biogas production was greatly increased with the initial grease waste
degradation by Pseudomonas aeruginosa.
Abstract: This research is to study the performance of heat
pump dryer for drying of kaffir lime leaves under different media and
to compare the color values and essential oil content of final products
after drying. In the experiments, kaffir lime leaves were dried in the
closed-loop system at drying temperatures of 40, 50 and 60 oC. The
drying media used in this study were hot air, CO2 and N2 gases. The
velocity of drying media in the drying chamber was 0.4 m/s with
bypass ratio of 30%. The initial moisture content of kaffir lime leaves
was approximately 180-190 % d.b. It was dried until down to a final
moisture content of 10% d.b. From the experiments, the results
showed that drying rate, the coefficient of performance (COP) and
specific energy consumption (SEC) depended on drying temperature.
While drying media did not affect on drying rate. The time for kaffir
lime leaves drying at 40, 50 and 60 oC was 10, 5 and 3 hours,
respectively. The performance of the heat pump system decreased
with drying temperature in the range of 2.20-3.51. In the aspect of
final product color, the greenness and overall color had a great
change under drying temperature at 60 oC rather than drying at 40
and 50 oC. When compared among drying media, the greenness and
overall color of product dried with hot air at 60 oC had a great change
rather than dried with CO2 and N2.
Abstract: In this paper the multi-mode resource-constrained project scheduling problem with discounted cash flows is considered. Minimizing the makespan and maximization the net present value (NPV) are the two common objectives that have been investigated in the literature. We apply one evolutionary algorithm named multiobjective particle swarm optimization (MOPSO) to find Pareto front solutions. We used standard sets of instances from the project scheduling problem library (PSPLIB). The results are computationally compared respect to different metrics taken from the literature on evolutionary multi-objective optimization.
Abstract: Summarizing skills have been introduced to English
syllabus in secondary school in Malaysia to evaluate student-s comprehension for a given text where it requires students to employ several strategies to produce the summary. This paper reports on our effort to develop a computer-based summarization assessment system
that detects the strategies used by the students in producing their
summaries. Sentence decomposition of expert-written summaries is
used to analyze how experts produce their summary sentences. From
the analysis, we identified seven summarizing strategies and their
rules which are then transformed into a set of heuristic rules on how
to determine the summarizing strategies. We developed an algorithm
based on the heuristic rules and performed some experiments to
evaluate and support the technique proposed.
Abstract: Nowadays, efficiency, effectiveness and economy are regarded as the main objectives of managers and the secret of the continuity of an organization in competing economy. In such competing settings, it is essential that the management of an organization has not been neglected and been obliged to identify quickly the opportunities for improving the operation of organization and remove the shortcomings of their managed system in order to use the opportunities for development. Operational auditing is a useful tool for system adjustment and leading an organization toward its objectives. Operational auditing is indeed a viewpoint which identifies the causes of insufficiencies, weaknesses and deficiencies of system and plans to eliminate them. Operational auditing is useful in the effectiveness and optimization of executive managers- decisions and increasing the efficiency and economy of their performance in the future and prevents the waste and incorrect use of resources. Evidence shows that operational auditing is used at a limited level in Iran. This matter raises some questions like the following ones in the minds. Why do a limited number of corporations use operational auditing? Which factors can guarantee its full implementation? What obstacles are there in its implementation? The purpose of this article is to determine executive objectives, the operation domain of operational auditing, the components of operational auditing and the executive obstacles to operational auditing in Iran.
Abstract: The theory of Groebner Bases, which has recently been
honored with the ACM Paris Kanellakis Theory and Practice Award,
has become a crucial building block to computer algebra, and is
widely used in science, engineering, and computer science. It is wellknown
that Groebner bases computation is EXP-SPACE in a general
polynomial ring setting.
However, for many important applications in computer science
such as satisfiability and automated verification of hardware and
software, computations are performed in a Boolean ring. In this paper,
we give an algorithm to show that Groebner bases computation is PSPACE
in Boolean rings. We also show that with this discovery,
the Groebner bases method can theoretically be as efficient as
other methods for automated verification of hardware and software.
Additionally, many useful and interesting properties of Groebner
bases including the ability to efficiently convert the bases for different
orders of variables making Groebner bases a promising method in
automated verification.
Abstract: This paper presents a cold chain monitoring system which focuses on assessment of quality and dynamic pricing information about food in cold chain. Cold chain is composed of many actors and stages; however it can be seen as a single entity since a breakdown in temperature control at any stage can impact the final quality of the product. In a cold chain, the shelf life, quality, and safety of perishable food throughout the supply chain is greatly impacted by environmental factors especially temperature. In this paper, a prototype application is implemented to retrieve timetemperature history, the current quality and the dynamic price setting according to changing quality impacted by temperature fluctuations in real-time.
Abstract: Work-life balance has been acknowledged and
promoted for the sake of employee retention. It is essential for a
manager to realize the human resources situation within a company to
help employees work happily and perform at their best. This paper
suggests knowledge management and critical thinking are useful to
motivate employees to think about their work-life balance. A
qualitative case study is presented, which aimed to discover the
meaning of work-life balance-s meaning from the perspective of Thai
knowledge workers and how it affects their decision-making towards
work resignation. Results found three types of work-life balance
dimensions; a work- life balance including a workplace and a private
life setting, an organizational working life balance only, and a worklife
balance only in a private life setting. These aspects all influenced
the decision-making of the employees. Factors within a theme of an
organizational work-life balance were involved with systematic
administration, fair treatment, employee recognition, challenging
assignments to gain working experience, assignment engagement,
teamwork, relationship with superiors, and working environment,
while factors concerning private life settings were about personal
demands such as an increasing their salary or starting their own
business.
Abstract: Traditional principal components analysis (PCA)
techniques for face recognition are based on batch-mode training
using a pre-available image set. Real world applications require that
the training set be dynamic of evolving nature where within the
framework of continuous learning, new training images are
continuously added to the original set; this would trigger a costly
continuous re-computation of the eigen space representation via
repeating an entire batch-based training that includes the old and new
images. Incremental PCA methods allow adding new images and
updating the PCA representation. In this paper, two incremental
PCA approaches, CCIPCA and IPCA, are examined and compared.
Besides, different learning and testing strategies are proposed and
applied to the two algorithms. The results suggest that batch PCA is
inferior to both incremental approaches, and that all CCIPCAs are
practically equivalent.
Abstract: Cosmic showers, from their places of origin in space,
after entering earth generate secondary particles called Extensive Air
Shower (EAS). Detection and analysis of EAS and similar High
Energy Particle Showers involve a plethora of experimental setups
with certain constraints for which soft-computational tools like
Artificial Neural Network (ANN)s can be adopted. The optimality
of ANN classifiers can be enhanced further by the use of Multiple
Classifier System (MCS) and certain data - dimension reduction
techniques. This work describes the performance of certain data
dimension reduction techniques like Principal Component Analysis
(PCA), Independent Component Analysis (ICA) and Self Organizing
Map (SOM) approximators for application with an MCS formed
using Multi Layer Perceptron (MLP), Recurrent Neural Network
(RNN) and Probabilistic Neural Network (PNN). The data inputs are
obtained from an array of detectors placed in a circular arrangement
resembling a practical detector grid which have a higher dimension
and greater correlation among themselves. The PCA, ICA and SOM
blocks reduce the correlation and generate a form suitable for real
time practical applications for prediction of primary energy and
location of EAS from density values captured using detectors in a
circular grid.
Abstract: Nowadays, ontologies are the only widely accepted paradigm for the management of sharable and reusable knowledge in a way that allows its automatic interpretation. They are collaboratively created across the Web and used to index, search and annotate documents. The vast majority of the ontology based approaches, however, focus on indexing texts at document level. Recently, with the advances in ontological engineering, it became clear that information indexing can largely benefit from the use of general purpose ontologies which aid the indexing of documents at word level. This paper presents a concept indexing algorithm, which adds ontology information to words and phrases and allows full text to be searched, browsed and analyzed at different levels of abstraction. This algorithm uses a general purpose ontology, OntoRo, and an ontologically tagged corpus, OntoCorp, both developed for the purpose of this research. OntoRo and OntoCorp are used in a two-stage supervised machine learning process aimed at generating ontology tagging rules. The first experimental tests show a tagging accuracy of 78.91% which is encouraging in terms of the further improvement of the algorithm.