Abstract: Data on 657 lactation from 163 Maltese goat,
collected over a 5-year period were analyzed by a mixed model to
estimate the variance components for heritability. The considered
lactation traits were: milk yield (MY) and lactation length (LL). Year,
parity and type of birth (single or twin) were significant sources of
variation for lactation length; on the other hand milk yield was
significantly influenced only by the year. The average MY was
352.34 kg and the average LL was 230 days. Estimates of heritability
were 0.21 and 0.15 for MY and LL respectively. These values
suggest there is low correlation between genotype and phenotype so
it may be difficult to evaluate animals directly on phenotype. So, the
genetic improvement of this breed may be quite slow without the
support of progeny test aimed to select Maltese breeders.
Abstract: A numerical study on the influence of electroosmotic flow on analyte preconcentration by isotachophoresis ( ITP) is made. We consider that the double layer induced electroosmotic flow ( EOF) counterbalance the electrophoretic velocity and a stationary ITP stacked zones results. We solve the Navier-Stokes equations coupled with the Nernst-Planck equations to determine the local convective velocity and the preconcentration dynamics of ions. Our numerical algorithm is based on a finite volume method along with a secondorder upwind scheme. The present numerical algorithm can capture the the sharp boundaries of step-changes ( plateau mode) or zones of steep gradients ( peak mode) accurately. The convection of ions due to EOF reduces the resolution of the ITP transition zones and produces a dispersion in analyte zones. The role of the electrokinetic parameters which induces dispersion is analyzed. A one-dimensional model for the area-averaged concentrations based on the Taylor-Aristype effective diffusivity is found to be in good agreement with the computed solutions.
Abstract: The paper presents a complete discrete statistical framework, based on a novel vector quantization (VQ) front-end process. This new VQ approach performs an optimal distribution of VQ codebook components on HMM states. This technique that we named the distributed vector quantization (DVQ) of hidden Markov models, succeeds in unifying acoustic micro-structure and phonetic macro-structure, when the estimation of HMM parameters is performed. The DVQ technique is implemented through two variants. The first variant uses the K-means algorithm (K-means- DVQ) to optimize the VQ, while the second variant exploits the benefits of the classification behavior of neural networks (NN-DVQ) for the same purpose. The proposed variants are compared with the HMM-based baseline system by experiments of specific Arabic consonants recognition. The results show that the distributed vector quantization technique increase the performance of the discrete HMM system.
Abstract: Previous studies mass evacuation route network does
not fully reflect the step-by-step behavior and evacuees make routing
decisions. Therefore, they do not work as expected when applied to the
evacuation route planning is valid. This article describes where
evacuees may have to make a direction to select all areas were
identified as guiding points to improve evacuation routes network.
This improved route network can be used as a basis for the layout can
be used to guide the signs indicate that provides the required
evacuation direction. This article also describes that combines
simulation and artificial bee colony algorithm to provide the proposed
routing solutions, to plan an integrated routing mode. The improved
network and the model used is the cinema as a case study to assess the
floor. The effectiveness of guidance solution in the total evacuation
time is significant by verification.
Abstract: Facial expression analysis is rapidly becoming an
area of intense interest in computer science and human-computer
interaction design communities. The most expressive way humans
display emotions is through facial expressions. In this paper we
present a method to analyze facial expression from images by
applying Gabor wavelet transform (GWT) and Discrete Cosine
Transform (DCT) on face images. Radial Basis Function (RBF)
Network is used to classify the facial expressions. As a second stage,
the images are preprocessed to enhance the edge details and non
uniform down sampling is done to reduce the computational
complexity and processing time. Our method reliably works even
with faces, which carry heavy expressions.
Abstract: A self tuning PID control strategy using reinforcement
learning is proposed in this paper to deal with the control of wind
energy conversion systems (WECS). Actor-Critic learning is used to
tune PID parameters in an adaptive way by taking advantage of the
model-free and on-line learning properties of reinforcement learning
effectively. In order to reduce the demand of storage space and to
improve the learning efficiency, a single RBF neural network is used
to approximate the policy function of Actor and the value function of
Critic simultaneously. The inputs of RBF network are the system
error, as well as the first and the second-order differences of error.
The Actor can realize the mapping from the system state to PID
parameters, while the Critic evaluates the outputs of the Actor and
produces TD error. Based on TD error performance index and
gradient descent method, the updating rules of RBF kernel function
and network weights were given. Simulation results show that the
proposed controller is efficient for WECS and it is perfectly
adaptable and strongly robust, which is better than that of a
conventional PID controller.
Abstract: Early supplier involvement (ESI) benefits new
product development projects several ways. Nevertheless, many castuser
companies do not know the advantages of ESI and therefore do
not utilize it. This paper presents reasons why to utilize ESI in
casting industry and how that can be done. Further, this paper
presents advantages and challenges related to ESI in casting industry,
and introduces a Casting-Network Collaboration Model. The model
presents practices for companies to build advantageous collaborative
relationships. More detailed, the model describes three levels for
company-network relationships in casting industry with different
degrees of collaboration, and requirements for operating in each
level. In our research, ESI was found to influence, for example, on
project time, component cost, and quality. In addition, challenges
related to ESI, such as, a lack of mutual trust and unawareness about
the advantages were found. Our research approach was a case study
including four cases.
Abstract: In this paper, a Cooperative Multi-robot for Carrying
Targets (CMCT) algorithm is proposed. The multi-robot team
consists of three robots, one is a supervisor and the others are
workers for carrying boxes in a store of 100×100 m2. Each robot has
a self recharging mechanism. The CMCT minimizes robot-s worked
time for carrying many boxes during day by working in parallel. That
is, the supervisor detects the required variables in the same time
another robots work with previous variables. It works with
straightforward mechanical models by using simple cosine laws. It
detects the robot-s shortest path for reaching the target position
avoiding obstacles by using a proposed CMCT path planning
(CMCT-PP) algorithm. It prevents the collision between robots
during moving. The robots interact in an ad hoc wireless network.
Simulation results show that the proposed system that consists of
CMCT algorithm and its accomplished CMCT-PP algorithm
achieves a high improvement in time and distance while performing
the required tasks over the already existed algorithms.
Abstract: In this paper, we present optimal control for
movement and trajectory planning for four degrees-of-freedom robot
using Fuzzy Logic (FL) and Genetic Algorithms (GAs). We have
evaluated using Fuzzy Logic (FL) and Genetic Algorithms (GAs)
for four degree-of-freedom (4 DOF) robotics arm, Uncertainties like;
Movement, Friction and Settling Time in robotic arm movement
have been compensated using Fuzzy logic and Genetic Algorithms.
The development of a fuzzy genetic optimization algorithm is
presented and discussed. The result are compared only GA and
Fuzzy GA. This paper describes genetic algorithms, which is
designed to optimize robot movement and trajectory. Though the
model represents is a general model for redundant structures and
could represent any n-link structures. The result is a complete
trajectory planning with Fuzzy logic and Genetic algorithms
demonstrating the flexibility of this technique of artificial
intelligence.
Abstract: This article addresses feature selection for breast
cancer diagnosis. The present process contains a wrapper approach
based on Genetic Algorithm (GA) and case-based reasoning (CBR).
GA is used for searching the problem space to find all of the possible
subsets of features and CBR is employed to estimate the evaluation
result of each subset. The results of experiment show that the
proposed model is comparable to the other models on Wisconsin
breast cancer (WDBC) dataset.
Abstract: With the rapid growth in business size, today's businesses orient towards electronic technologies. Amazon.com and e-bay.com are some of the major stakeholders in this regard. Unfortunately the enormous size and hugely unstructured data on the web, even for a single commodity, has become a cause of ambiguity for consumers. Extracting valuable information from such an everincreasing data is an extremely tedious task and is fast becoming critical towards the success of businesses. Web content mining can play a major role in solving these issues. It involves using efficient algorithmic techniques to search and retrieve the desired information from a seemingly impossible to search unstructured data on the Internet. Application of web content mining can be very encouraging in the areas of Customer Relations Modeling, billing records, logistics investigations, product cataloguing and quality management. In this paper we present a review of some very interesting, efficient yet implementable techniques from the field of web content mining and study their impact in the area specific to business user needs focusing both on the customer as well as the producer. The techniques we would be reviewing include, mining by developing a knowledge-base repository of the domain, iterative refinement of user queries for personalized search, using a graphbased approach for the development of a web-crawler and filtering information for personalized search using website captions. These techniques have been analyzed and compared on the basis of their execution time and relevance of the result they produced against a particular search.
Abstract: Both software applications and their development environment are becoming more and more distributed. This trend impacts not only the way software computes, but also how it looks. This article proposes a Human Computer Interface (HCI) template from three representative applications we have developed. These applications include a Multi-Agent System based software, a 3D Internet computer game with distributed game world logic, and a programming language environment used in constructing distributed neural network and its visualizations. HCI concepts that are common to these applications are described in abstract terms in the template. These include off-line presentation of global entities, entities inside a hierarchical namespace, communication and languages, reconfiguration of entity references in a graph, impersonation and access right, etc. We believe the metaphor that underlies an HCI concept as well as the relationships between a bunch of HCI concepts are crucial to the design of software systems and vice versa.
Abstract: This paper is a description approach to predict
incoming and outgoing data rate in network system by using
association rule discover, which is one of the data mining
techniques. Information of incoming and outgoing data in each
times and network bandwidth are network performance
parameters, which needed to solve in the traffic problem. Since
congestion and data loss are important network problems. The result
of this technique can predicted future network traffic. In addition,
this research is useful for network routing selection and network
performance improvement.
Abstract: Recent advancements in sensor technologies and
Wireless Body Area Networks (WBANs) have led to the
development of cost-effective healthcare devices which can be used
to monitor and analyse a person-s physiological parameters from
remote locations. These advancements provides a unique opportunity
to overcome current healthcare challenges of low quality service
provisioning, lack of easy accessibility to service varieties, high costs
of services and increasing population of the elderly experienced
globally. This paper reports on a prototype implementation of an
architecture that seamlessly integrates Wireless Body Area Network
(WBAN) with Web services (WS) to proactively collect
physiological data of remote patients to recommend diagnostic
services. Technologies based upon WBAN and WS can provide
ubiquitous accessibility to a variety of services by allowing
distributed healthcare resources to be massively reused to provide
cost-effective services without individuals physically moving to the
locations of those resources. In addition, these technologies can
reduce costs of healthcare services by allowing individuals to access
services to support their healthcare. The prototype uses WBAN body
sensors implemented on arduino fio platforms to be worn by the
patient and an android smart phone as a personal server. The
physiological data are collected and uploaded through GPRS/internet
to the Medical Health Server (MHS) to be analysed. The prototype
monitors the activities, location and physiological parameters such as
SpO2 and Heart Rate of the elderly and patients in rehabilitation.
Medical practitioners would have real time access to the uploaded
information through a web application.
Abstract: The PAX6, a transcription factor, is essential for the morphogenesis of the eyes, brain, pituitary and pancreatic islets. In rodents, the loss of Pax6 function leads to central nervous system defects, anophthalmia, and nasal hypoplasia. The haplo-insufficiency of Pax6 causes microphthalmia, aggression and other behavioral abnormalities. It is also required in brain patterning and neuronal plasticity. In human, heterozygous mutation of Pax6 causes loss of iris [aniridia], mental retardation and glucose intolerance. The 3- deletion in Pax6 leads to autism and aniridia. The phenotypes are variable in peneterance and expressivity. However, mechanism of function and interaction of PAX6 with other proteins during development and associated disease are not clear. It is intended to explore interactors of PAX6 to elucidated biology of PAX6 function in the tissues where it is expressed and also in the central regulatory pathway. This report describes In-silico approaches to explore interacting proteins of PAX6. The models show several possible proteins interacting with PAX6 like MITF, SIX3, SOX2, SOX3, IPO13, TRIM, and OGT. Since the Pax6 is a critical transcriptional regulator and master control gene of eye and brain development it might be interacting with other protein involved in morphogenesis [TGIF, TGF, Ras etc]. It is also presumed that matricelluar proteins [SPARC, thrombospondin-1 and osteonectin etc] are likely to interact during transport and processing of PAX6 and are somewhere its cascade. The proteins involved in cell survival and cell proliferation can also not be ignored.
Abstract: Gas turbine air inlet cooling is a useful method for
increasing output for regions where significant power demand and
highest electricity prices occur during the warm months. Inlet air
cooling increases the power output by taking advantage of the gas
turbine-s feature of higher mass flow rate when the compressor inlet
temperature decreases. Different methods are available for reducing
gas turbine inlet temperature. There are two basic systems currently
available for inlet cooling. The first and most cost-effective system is
evaporative cooling. Evaporative coolers make use of the evaporation
of water to reduce the gas turbine-s inlet air temperature. The second
system employs various ways to chill the inlet air. In this method, the
cooling medium flows through a heat exchanger located in the inlet
duct to remove heat from the inlet air. However, the evaporative
cooling is limited by wet-bulb temperature while the chilling can cool
the inlet air to temperatures that are lower than the wet bulb
temperature. In the present work, a thermodynamic model of a gas
turbine is built to calculate heat rate, power output and thermal
efficiency at different inlet air temperature conditions. Computational
results are compared with ISO conditions herein called "base-case".
Therefore, the two cooling methods are implemented and solved for
different inlet conditions (inlet temperature and relative humidity).
Evaporative cooler and absorption chiller systems results show that
when the ambient temperature is extremely high with low relative
humidity (requiring a large temperature reduction) the chiller is the
more suitable cooling solution. The net increment in the power output
as a function of the temperature decrease for each cooling method is
also obtained.
Abstract: Palm shell obtained from coastal part of southern
India was studied for the removal for the adsorption of Hg (II) ions.
Batch adsorption experiments were carried out as a function of pH,
concentration of Hg (II) ions, time, temperature and adsorbent dose.
Maximum removal was seen in the range pH 4.0- pH 7.0. The palm
shell powder used as adsorbent was characterized for its surface area,
SEM, PXRD, FTIR, ion exchange capacity, moisture content, and
bulk density, soluble content in water and acid and pH. The
experimental results were analyzed using Langmuir I, II, III, IV and
Freundlich adsorption isotherms. The batch sorption kinetics was
studied for the first order reversible reaction, pseudo first order;
pseudo second order reaction and the intra-particle diffusion reaction.
The biomass was successfully used for removal Hg (II) from
synthetic and industrial effluents and the technique appears
industrially applicable and viable.
Abstract: Combinatorial optimization problems arise in many scientific and practical applications. Therefore many researchers try to find or improve different methods to solve these problems with high quality results and in less time. Genetic Algorithm (GA) and Simulated Annealing (SA) have been used to solve optimization problems. Both GA and SA search a solution space throughout a sequence of iterative states. However, there are also significant differences between them. The GA mechanism is parallel on a set of solutions and exchanges information using the crossover operation. SA works on a single solution at a time. In this work SA and GA are combined using new technique in order to overcome the disadvantages' of both algorithms.
Abstract: While the form of crises may change, their essence
remains the same (such as a cycle of abundant liquidity, rapid credit
growth, and a low-inflation environment followed by an asset-price
bubble). The current market turbulence began in mid-2000s when the
US economy shifted to imbalanced both internal and external
macroeconomic positions. We see two key causes of these problems
– loose US monetary policy in early 2000s and US government
guarantees issued on the securities by government-sponsored
enterprises what was further fueled by financial innovations such as
structured credit products. We have discovered both negative and
positive lessons deriving from this crisis and divided the negative
lessons into three groups: financial products and valuation, processes
and business models, and strategic issues. Moreover, we address key
risk management lessons and exit strategies derived from the current
crisis and recommend policies that should help diminish the negative
impact of future potential crises.
Abstract: This paper presents a novel algorithm of stereo
correspondence with rank transform. In this algorithm we used the
genetic algorithm to achieve the accurate disparity map. Genetic
algorithms are efficient search methods based on principles of
population genetic, i.e. mating, chromosome crossover, gene
mutation, and natural selection. Finally morphology is employed to
remove the errors and discontinuities.