Abstract: Temperature is one of the most principle factors affects aquaculture system. It can cause stress and mortality or superior environment for growth and reproduction. This paper presents the control of pond water temperature using artificial intelligence technique. The water temperature is very important parameter for shrimp growth. The required temperature for optimal growth is 34oC, if temperature increase up to 38oC it cause death of the shrimp, so it is important to control water temperature. Solar thermal water heating system is designed to supply an aquaculture pond with the required hot water in Mersa Matruh in Egypt. Neural networks are massively parallel processors that have the ability to learn patterns through a training experience. Because of this feature, they are often well suited for modeling complex and non-linear processes such as those commonly found in the heating system. Artificial neural network is proposed to control water temperature due to Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques. They have been used to solve complicated practical problems. Moreover this paper introduces a complete mathematical modeling and MATLAB SIMULINK model for the aquaculture system. The simulation results indicate that, the control unit success in keeping water temperature constant at the desired temperature by controlling the hot water flow rate.
Abstract: Optimization and control of reactive power
distribution in the power systems leads to the better operation of the
reactive power resources. Reactive power control reduces
considerably the power losses and effective loads and improves the
power factor of the power systems. Another important reason of the
reactive power control is improving the voltage profile of the power
system. In this paper, voltage and reactive power control using
Neural Network techniques have been applied to the 33 shines-
Tehran Electric Company. In this suggested ANN, the voltages of PQ
shines have been considered as the input of the ANN. Also, the
generators voltages, tap transformers and shunt compensators have
been considered as the output of ANN. Results of this techniques
have been compared with the Linear Programming. Minimization of
the transmission line power losses has been considered as the
objective function of the linear programming technique. The
comparison of the results of the ANN technique with the LP shows
that the ANN technique improves the precision and reduces the
computation time. ANN technique also has a simple structure and
this causes to use the operator experience.
Abstract: Semantic query optimization consists in restricting the
search space in order to reduce the set of objects of interest for a
query. This paper presents an indexing method based on UB-trees
and a static analysis of the constraints associated to the views of the
database and to any constraint expressed on attributes. The result of
the static analysis is a partitioning of the object space into disjoint
blocks. Through Space Filling Curve (SFC) techniques, each
fragment (block) of the partition is assigned a unique identifier,
enabling the efficient indexing of fragments by UB-trees. The search
space corresponding to a range query is restricted to a subset of the
blocks of the partition. This approach has been developed in the
context of a KB-DBMS but it can be applied to any relational
system.
Abstract: In situ observation of absorption spectral change of
heptil viologen cation radical (HV+.) was performed by slab optical
waveguide (SOWG) spectroscopy utilizing indium-tin-oxide (ITO)
electrodes. Synchronizing with electrochemical techniques, we
observed the adsorption process of HV+.on the ITO electrode. In this
study, we carried out the ITO-SOWG observations using KBr aqueous
solution containing different concentration of HV to investigate the
concentration dependent spectral change. A few specific absorption
bands, which indicated HV+.existed as both monomer and dimer on
ITO electrode surface with a monolayer or a few layers deposition,
were observed in UV-visible region. The change in the peak position
of the absorption spectra from adsorption species of HV+. were
correlated with the concentration of HV as well as the electrode
potential.
Abstract: Data mining, which is the exploration of
knowledge from the large set of data, generated as a result of
the various data processing activities. Frequent Pattern Mining
is a very important task in data mining. The previous
approaches applied to generate frequent set generally adopt
candidate generation and pruning techniques for the
satisfaction of the desired objective. This paper shows how
the different approaches achieve the objective of frequent
mining along with the complexities required to perform the
job. This paper will also look for hardware approach of cache
coherence to improve efficiency of the above process. The
process of data mining is helpful in generation of support
systems that can help in Management, Bioinformatics,
Biotechnology, Medical Science, Statistics, Mathematics,
Banking, Networking and other Computer related
applications. This paper proposes the use of both upward and
downward closure property for the extraction of frequent item
sets which reduces the total number of scans required for the
generation of Candidate Sets.
Abstract: One of the mayor problems of programming a cruise
circuit is to decide which destinations to include and which don-t.
Thus a decision problem emerges, that might be solved using a linear
and goal programming approach. The problem becomes more
complex if several boats in the fleet must be programmed in a limited
schedule, trying their capacity matches best a seasonal demand and
also attempting to minimize the operation costs. Moreover, the
programmer of the company should consider the time of the
passenger as a limited asset, and would like to maximize its usage.
The aim of this work is to design a method in which, using linear and
goal programming techniques, a model to design circuits for the
cruise company decision maker can achieve an optimal solution
within the fleet schedule.
Abstract: Probability-based identity disclosure risk
measurement may give the same overall risk for different
anonymization strategy of the same dataset. Some entities in the
anonymous dataset may have higher identification risks than the
others. Individuals are more concerned about higher risks than the
average and are more interested to know if they have a possibility of
being under higher risk. A notation of overall risk in the above
measurement method doesn-t indicate whether some of the involved
entities have higher identity disclosure risk than the others. In this
paper, we have introduced an identity disclosure risk measurement
method that not only implies overall risk, but also indicates whether
some of the members have higher risk than the others. The proposed
method quantifies the overall risk based on the individual risk values,
the percentage of the records that have a risk value higher than the
average and how larger the higher risk values are compared to the
average. We have analyzed the disclosure risks for different
disclosure control techniques applied to original microdata and
present the results.
Abstract: The performances of small and medium enterprises
have stagnated in the last two decades. This has mainly been due to
the emergence of HIV / Aids. The disease has had a detrimental
effect on the general economy of the country leading to morbidity
and mortality of the Kenyan workforce in their primary age. The
present study sought to establish the economic impact of HIV / Aids
on the micro-enterprise development in Obunga slum – Kisumu, in
terms of production loss, increasing labor related cost and to establish
possible strategies to address the impact of HIV / Aids on microenterprises.
The study was necessitated by the observation that most
micro-enterprises in the slum are facing severe economic and social
crisis due to the impact of HIV / Aids, they get depleted and close
down within a short time due to death of skilled and experience
workforce. The study was carried out between June 2008 and June
2009 in Obunga slum. Data was subjected to computer aided
statistical analysis that included descriptive statistic, chi-squared and
ANOVA techniques. Chi-squared analysis on the micro-enterprise
owners opinion on the impact of HIV / Aids on depletion of microenterprise
compared to other diseases indicated high levels of the
negative effects of the disease at significance levels of P
Abstract: XML is an important standard of data exchange and
representation. As a mature database system, using relational database
to support XML data may bring some advantages. But storing XML in
relational database has obvious redundancy that wastes disk space,
bandwidth and disk I/O when querying XML data. For the efficiency
of storage and query XML, it is necessary to use compressed XML
data in relational database. In this paper, a compressed relational
database technology supporting XML data is presented. Original
relational storage structure is adaptive to XPath query process. The
compression method keeps this feature. Besides traditional relational
database techniques, additional query process technologies on
compressed relations and for special structure for XML are presented.
In this paper, technologies for XQuery process in compressed
relational database are presented..
Abstract: Content-Based Image Retrieval (CBIR) has been
one on the most vivid research areas in the field of computer vision
over the last 10 years. Many programs and tools have been
developed to formulate and execute queries based on the visual or
audio content and to help browsing large multimedia repositories.
Still, no general breakthrough has been achieved with respect to
large varied databases with documents of difering sorts and with
varying characteristics. Answers to many questions with respect to
speed, semantic descriptors or objective image interpretations are
still unanswered. In the medical field, images, and especially
digital images, are produced in ever increasing quantities and used
for diagnostics and therapy. In several articles, content based
access to medical images for supporting clinical decision making
has been proposed that would ease the management of clinical data
and scenarios for the integration of content-based access methods
into Picture Archiving and Communication Systems (PACS) have
been created. This paper gives an overview of soft computing
techniques. New research directions are being defined that can
prove to be useful. Still, there are very few systems that seem to be
used in clinical practice. It needs to be stated as well that the goal
is not, in general, to replace text based retrieval methods as they
exist at the moment.
Abstract: In this paper, a novel approach for robust trajectory tracking of induction motor drive is presented. By combining variable structure systems theory with fuzzy logic concept and neural network techniques, a new algorithm is developed. Fuzzy logic was used for the adaptation of the learning algorithm to improve the robustness of learning and operating of the neural network. The developed control algorithm is robust to parameter variations and external influences. It also assures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the designed controller of induction motor drives which considered as highly non linear dynamic complex systems and variable characteristics over the operating conditions.
Abstract: The particular interests of this paper is to explore if the simple Genetic Algorithms (GA) starts with population of only two individuals and applying different crossover technique over these parents to produced 104 children, each one has different attributes inherited from their parents; is better than starting with population of 100 individuals; and using only one type crossover (order crossover OX). For this reason we implement GA with 52 different crossover techniques; each one produce two children; which means 104 different children will be produced and this may discover more search space, also we implement classic GA with order crossover and many experiments were done over 3 Travel Salesman Problem (TSP) to find out which method is better, and according to the results we can say that GA with Multi-crossovers is much better.
Abstract: Horizontal wells are proven to be better producers
because they can be extended for a long distance in the pay zone.
Engineers have the technical means to forecast the well productivity
for a given horizontal length. However, experiences have shown that
the actual production rate is often significantly less than that of
forecasted. It is a difficult task, if not impossible to identify the real
reason why a horizontal well is not producing what was forecasted.
Often the source of problem lies in the drilling of horizontal section
such as permeability reduction in the pay zone due to mud invasion
or snaky well patterns created during drilling. Although drillers aim
to drill a constant inclination hole in the pay zone, the more frequent
outcome is a sinusoidal wellbore trajectory. The two factors, which
play an important role in wellbore tortuosity, are the inclination and
side force at bit. A constant inclination horizontal well can only be
drilled if the bit face is maintained perpendicular to longitudinal axis
of bottom hole assembly (BHA) while keeping the side force nil at
the bit. This approach assumes that there exists no formation force at
bit. Hence, an appropriate BHA can be designed if bit side force and
bit tilt are determined accurately. The Artificial Neural Network
(ANN) is superior to existing analytical techniques. In this study, the
neural networks have been employed as a general approximation tool
for estimation of the bit side forces. A number of samples are
analyzed with ANN for parameters of bit side force and the results
are compared with exact analysis. Back Propagation Neural network
(BPN) is used to approximation of bit side forces. Resultant low
relative error value of the test indicates the usability of the BPN in
this area.
Abstract: In this paper, an approach to reduce the computation steps required by fast neural networksfor the searching process is presented. The principle ofdivide and conquer strategy is applied through imagedecomposition. Each image is divided into small in sizesub-images and then each one is tested separately usinga fast neural network. The operation of fast neuralnetworks based on applying cross correlation in thefrequency domain between the input image and theweights of the hidden neurons. Compared toconventional and fast neural networks, experimentalresults show that a speed up ratio is achieved whenapplying this technique to locate human facesautomatically in cluttered scenes. Furthermore, fasterface detection is obtained by using parallel processingtechniques to test the resulting sub-images at the sametime using the same number of fast neural networks. Incontrast to using only fast neural networks, the speed upratio is increased with the size of the input image whenusing fast neural networks and image decomposition.
Abstract: Although, it is a long time that human know about
the importance of environment in life, but at the last decade of 20
century, the space that was full of hot scientific, collegial and
political were made in environmental challenge, So much that, this
problem not only disarrange the peace and security of life, but also it
has threatened human existence. One of the problems in last years
that are significant for authorities is unsatisfactory achieved results
against of using huge cost for magnificent environmental projects.
This subject leads thinker to this thought that for solving the
environmental problems it is needed new methods include of
sociology, ethics and philosophic, etc. methods apart of technical
affairs. Environment ethics is a new branch of philosophic ethics
discussion that discusses about the ethics relationship between
humans and universe that is around them. By notifying to the above
considered affairs, in today world, necessity of environmental ethics
for environment management is reduplicated. In the following the
article has been focused on environmental ethics role and
environmental management methods and techniques for developing
it.
Abstract: Locality Sensitive Hashing (LSH) is one of the most
promising techniques for solving nearest neighbour search problem in
high dimensional space. Euclidean LSH is the most popular variation
of LSH that has been successfully applied in many multimedia
applications. However, the Euclidean LSH presents limitations that
affect structure and query performances. The main limitation of the
Euclidean LSH is the large memory consumption. In order to achieve
a good accuracy, a large number of hash tables is required. In this
paper, we propose a new hashing algorithm to overcome the storage
space problem and improve query time, while keeping a good
accuracy as similar to that achieved by the original Euclidean LSH.
The Experimental results on a real large-scale dataset show that the
proposed approach achieves good performances and consumes less
memory than the Euclidean LSH.
Abstract: Robotic system is an important area in artificial intelligence that aims at developing the performance techniques of the robot and making it more efficient and more effective in choosing its correct behavior. In this paper the distributed learning classifier system is used for designing a simulated control system for robot to perform complex behaviors. A set of enhanced approaches that support default hierarchies formation is suggested and compared with each other in order to make the simulated robot more effective in mapping the input to the correct output behavior.
Abstract: XML is becoming a de facto standard for online data exchange. Existing XML filtering techniques based on a publish/subscribe model are focused on the highly structured data marked up with XML tags. These techniques are efficient in filtering the documents of data-centric XML but are not effective in filtering the element contents of the document-centric XML. In this paper, we propose an extended XPath specification which includes a special matching character '%' used in the LIKE operation of SQL in order to solve the difficulty of writing some queries to adequately filter element contents using the previous XPath specification. We also present a novel technique for filtering a collection of document-centric XMLs, called Pfilter, which is able to exploit the extended XPath specification. We show several performance studies, efficiency and scalability using the multi-query processing time (MQPT).
Abstract: Human pose estimation can be executed using Active Shape Models. The existing techniques for applying to human-body research using Active Shape Models, such as human detection, primarily take the form of silhouette of human body. This technique is not able to estimate accurately for human pose to concern two arms and legs, as the silhouette of human body represents the shape as out of round. To solve this problem, we applied the human body model as stick-figure, “skeleton". The skeleton model of human body can give consideration to various shapes of human pose. To obtain effective estimation result, we applied background subtraction and deformed matching algorithm of primary Active Shape Models in the fitting process. The images which were used to make the model were 600 human bodies, and the model has 17 landmark points which indicate body junction and key features of human pose. The maximum iteration for the fitting process was 30 times and the execution time was less than .03 sec.
Abstract: This paper reports a new application of material accounting techniques to characterise and quantify material stocks and flows at the “neighbourhood" scale. The study area is the main campus of the University of New South Wales in Sydney, Australia. The system boundary is defined by the urban structural unit (USU), a typological construct devised to facilitate assessment of the metabolism of urban systems. A streamlined material flow analysis (MFA) was applied to quantify the stocks and flows of key construction materials within the campus USU over time, drawing on empirical data from a major campus development project. The results are reviewed to assess the efficacy of the method in supporting urban environmental evaluation and design practice, for example to facilitate estimation of significant impacts such as greenhouse gas emissions. It is concluded that linking a service (in this case, teaching students) enabled by a given product (university buildings) to the amount of materials used in creating that product offers a potential way to reduce the environmental impact of that service, through more efficient use of materials.