Abstract: In the oil and gas industry, energy prediction can help
the distributor and customer to forecast the outgoing and incoming
gas through the pipeline. It will also help to eliminate any
uncertainties in gas metering for billing purposes. The objective of
this paper is to develop Neural Network Model for energy
consumption and analyze the performance model. This paper
provides a comprehensive review on published research on the
energy consumption prediction which focuses on structures and the
parameters used in developing Neural Network models. This paper is
then focused on the parameter selection of the neural network
prediction model development for energy consumption and analysis
on the result. The most reliable model that gives the most accurate
result is proposed for the prediction. The result shows that the
proposed neural network energy prediction model is able to
demonstrate an adequate performance with least Root Mean Square
Error.
Abstract: Climate change has profound consequences for the agriculture of south-eastern Australia and its climate-induced water shortage in the Murray-Darling Basin. Post Keynesian Economics (PKE) macro-dynamics, along with Kaleckian investment and growth theory, are used to develop an ecological-economic system dynamics model of this complex nonlinear river basin system. The Murray- Darling Basin Simulation Model (MDB-SM) uses the principles of PKE to incorporate the fundamental uncertainty of economic behaviors of farmers regarding the investments they make and the climate change they face, particularly as regards water ecosystem services. MDB-SM provides a framework for macroeconomic policies, especially for long-term fiscal policy and for policy directed at the sustainability of agricultural water, as measured by socio-economic well-being considerations, which include sustainable consumption and investment in the river basin. The model can also reproduce other ecological and economic aspects and, for certain parameters and initial values, exhibit endogenous business cycles and ecological sustainability with realistic characteristics. Most importantly, MDBSM provides a platform for the analysis of alternative economic policy scenarios. These results reveal the importance of understanding water ecosystem adaptation under climate change by integrating a PKE macroeconomic analytical framework with the system dynamics modelling approach. Once parameterised and supplied with historical initial values, MDB-SM should prove to be a practical tool to provide alternative long-term policy simulations of agricultural water and socio-economic well-being.
Abstract: This paper proposes an algorithm which automatically aligns and stitches the component medical images (fluoroscopic) with varying degrees of overlap into a single composite image. The alignment method is based on similarity measure between the component images. As applied here the technique is intensity based rather than feature based. It works well in domains where feature based methods have difficulty, yet more robust than traditional correlation. Component images are stitched together using the new triangular averaging based blending algorithm. The quality of the resultant image is tested for photometric inconsistencies and geometric misalignments. This method cannot correct rotational, scale and perspective artifacts.
Abstract: Pigeon pea (Cajanus cajan) blanched for 20min was dehulled and milled into flour. The flour was incorporated into dried whole fermented maize (Ogi) at five levels. The resultant products were analyzed for chemical and pasting properties. The fortified Ogi samples were also assessed for sensory attributes: appearance, color, flavor, mouth feel and overall acceptability. The protein content in the whole Ogi fortified samples was in the range of 11.2-16.6% and crude fibre 3.22-3.46%. Fortified whole Ogi with pigeon pea at 30%, 40% and 50% of inclusion with pigeon pea flour has higher protein, crude fibre and ash content. Varying range of pasting quality was recorded for the blends, pasting temperature for fortified Obi was in the range of 45.3-49.50C and peak time 5.05-5.210C. The sensory acceptability of the whole Ogi fortified blends prepared into gruel has higher acceptability for various qualities in comparison with the traditional Ogi gruel.
Abstract: The concept of order reduction by least-squares moment matching and generalised least-squares methods has been extended about a general point ?a?, to obtain the reduced order models for linear, time-invariant dynamic systems. Some heuristic criteria have been employed for selecting the linear shift point ?a?, based upon the means (arithmetic, harmonic and geometric) of real parts of the poles of high order system. It is shown that the resultant model depends critically on the choice of linear shift point ?a?. The validity of the criteria is illustrated by solving a numerical example and the results are compared with the other existing techniques.
Abstract: This research work proposed a study of fruit bruise detection by means of a biospeckle method, selecting the papaya fruit (Carica papaya) as testing body. Papaya is recognized as a fruit of outstanding nutritional qualities, showing high vitamin A content, calcium, carbohydrates, exhibiting high popularity all over the world, considering consumption and acceptability. The commercialization of papaya faces special problems which are associated to bruise generation during harvesting, packing and transportation. Papaya is classified as climacteric fruit, permitting to be harvested before the maturation is completed. However, by one side bruise generation is partially controlled once the fruit flesh exhibits high mechanical firmness. By the other side, mechanical loads can set a future bruise at that maturation stage, when it can not be detected yet by conventional methods. Mechanical damages of fruit skin leave an entrance door to microorganisms and pathogens, which will cause severe losses of quality attributes. Traditional techniques of fruit quality inspection include total soluble solids determination, mechanical firmness tests, visual inspections, which would hardly meet required conditions for a fully automated process. However, the pertinent literature reveals a new method named biospeckle which is based on the laser reflectance and interference phenomenon. The laser biospeckle or dynamic speckle is quantified by means of the Moment of Inertia, named after its mechanical counterpart due to similarity between the defining formulae. Biospeckle techniques are able to quantify biological activities of living tissues, which has been applied to seed viability analysis, vegetable senescence and similar topics. Since the biospeckle techniques can monitor tissue physiology, it could also detect changes in the fruit caused by mechanical damages. The proposed technique holds non invasive character, being able to generate numerical results consistent with an adequate automation. The experimental tests associated to this research work included the selection of papaya fruit at different maturation stages which were submitted to artificial mechanical bruising tests. Damages were visually compared with the frequency maps yielded by the biospeckle technique. Results were considered in close agreement.
Abstract: K-Means (KM) is considered one of the major
algorithms widely used in clustering. However, it still has some
problems, and one of them is in its initialization step where it is
normally done randomly. Another problem for KM is that it
converges to local minima. Genetic algorithms are one of the
evolutionary algorithms inspired from nature and utilized in the field
of clustering. In this paper, we propose two algorithms to solve the
initialization problem, Genetic Algorithm Initializes KM (GAIK) and
KM Initializes Genetic Algorithm (KIGA). To show the effectiveness
and efficiency of our algorithms, a comparative study was done
among GAIK, KIGA, Genetic-based Clustering Algorithm (GCA),
and FCM [19].
Abstract: In this paper, we propose improved versions of DVHop
algorithm as QDV-Hop algorithm and UDV-Hop algorithm for
better localization without the need for additional range measurement
hardware. The proposed algorithm focuses on third step of DV-Hop,
first error terms from estimated distances between unknown node and
anchor nodes is separated and then minimized. In the QDV-Hop
algorithm, quadratic programming is used to minimize the error to
obtain better localization. However, quadratic programming requires
a special optimization tool box that increases computational
complexity. On the other hand, UDV-Hop algorithm achieves
localization accuracy similar to that of QDV-Hop by solving
unconstrained optimization problem that results in solving a system
of linear equations without much increase in computational
complexity. Simulation results show that the performance of our
proposed schemes (QDV-Hop and UDV-Hop) is superior to DV-Hop
and DV-Hop based algorithms in all considered scenarios.
Abstract: The Address Resolution Protocol (ARP) is used by
computers to map logical addresses (IP) to physical addresses
(MAC). However ARP is an all trusting protocol and is stateless
which makes it vulnerable to many ARP cache poisoning attacks
such as Man-in-the-Middle (MITM) and Denial of service (DoS)
attacks. These flaws result in security breaches thus weakening the
appeal of the computer for exchange of sensitive data. In this paper
we describe ARP, outline several possible ARP cache poisoning
attacks and give the detailed of some attack scenarios in network
having both wired and wireless hosts. We have analyzed each of
proposed solutions, identify their strengths and limitations. Finally
get that no solution offers a feasible solution. Hence, this paper
presents an efficient and secure version of ARP that is able to cope
up with all these types of attacks and is also a feasible solution. It is a
stateful protocol, by storing the information of the Request frame in
the ARP cache, to reduce the chances of various types of attacks in
ARP. It is more efficient and secure by broadcasting ARP Reply
frame in the network and storing related entries in the ARP cache
each time when communication take place.
Abstract: This paper attempts to highlight the significant role of
knowledge management practices (KMP) and competencies in
improving the performance and efficiency of public sector
organizations. It appears that public sector organizations in
developing countries have not received much attention in the
research literature of knowledge management and competencies.
Therefore, this paper seeks to explore the role of KMP and
competencies in achieving superior performance among public sector
organizations in Malaysia in the broader perspective. Survey
questionnaires were distributed to all Administrative and Diplomatic
Officers (ADS) from 28 ministries located in Putrajaya, Malaysia.
This paper also examines preliminary empirical results on the
relationship between support for knowledge management practices,
competencies, and orientation in Malaysia-s public organizations.
This paper supports the notion that the practices of knowledge
management at the organizational level are a prerequisite for
successful organizational performance. In conclusion, the results not
only have the potential to contribute theoretically to both
management strategy and knowledge management field literature but
also to the area of organizational performance.
Abstract: Geometric design is an important part of planning
process design for physical highway to fill up basic function of roads,
to give good traffic service. It is found that most of the road safety
problems occur at the horizontal curves and complex-compound
curves. In this paper, review on Sagarinn-Myinsain Portion of Nay
Pyi Taw - Mandalay highway has been conducted in aspect of
geometric design induced road safety condition. Horizontal
alignment of geometric features and curve details are reviewed based
on (AASHTO) standard and revised by Autodesk Land Desktop
Software. Moreover, 85th Percentile Operation Speeds (V85) with
driver confidence on horizontal curves is evaluated in order to obtain
the range of highway safety factor (FS). The length of the selected
highway portion is 13.65 miles and 8 lanes. The results of this study
can be used to investigate the possible hazardous locations in
advance and to revise how design radius and super elevation should
be for better road safety performance for the selected portion.
Moreover, the relationship between highway safety and highway
geometry characteristics can also be known.
Abstract: We report in this paper the procedure of a system of
automatic speech recognition based on techniques of the dynamic
programming. The technique of temporal retiming is a technique
used to synchronize between two forms to compare. We will see how
this technique is adapted to the field of the automatic speech
recognition. We will expose, in a first place, the theory of the
function of retiming which is used to compare and to adjust an
unknown form with a whole of forms of reference constituting the
vocabulary of the application. Then we will give, in the second place,
the various algorithms necessary to their implementation on machine.
The algorithms which we will present were tested on part of the
corpus of words in Arab language Arabdic-10 [4] and gave whole
satisfaction. These algorithms are effective insofar as we apply them
to the small ones or average vocabularies.
Abstract: Due to new distributed database applications such as
huge deductive database systems, the search complexity is constantly
increasing and we need better algorithms to speedup traditional
relational database queries. An optimal dynamic programming
method for such high dimensional queries has the big disadvantage of
its exponential order and thus we are interested in semi-optimal but
faster approaches. In this work we present a multi-agent based
mechanism to meet this demand and also compare the result with
some commonly used query optimization algorithms.
Abstract: This paper is concerned with the production of an Arabic word semantic similarity benchmark dataset. It is the first of its kind for Arabic which was particularly developed to assess the accuracy of word semantic similarity measurements. Semantic similarity is an essential component to numerous applications in fields such as natural language processing, artificial intelligence, linguistics, and psychology. Most of the reported work has been done for English. To the best of our knowledge, there is no word similarity measure developed specifically for Arabic. In this paper, an Arabic benchmark dataset of 70 word pairs is presented. New methods and best possible available techniques have been used in this study to produce the Arabic dataset. This includes selecting and creating materials, collecting human ratings from a representative sample of participants, and calculating the overall ratings. This dataset will make a substantial contribution to future work in the field of Arabic WSS and hopefully it will be considered as a reference basis from which to evaluate and compare different methodologies in the field.
Abstract: The performance of sensor-less controlled induction
motor drive depends on the accuracy of the estimated speed.
Conventional estimation techniques being mathematically complex
require more execution time resulting in poor dynamic response. The
nonlinear mapping capability and powerful learning algorithms of
neural network provides a promising alternative for on-line speed
estimation. The on-line speed estimator requires the NN model to be
accurate, simpler in design, structurally compact and computationally
less complex to ensure faster execution and effective control in real
time implementation. This in turn to a large extent depends on the
type of Neural Architecture. This paper investigates three types of
neural architectures for on-line speed estimation and their
performance is compared in terms of accuracy, structural
compactness, computational complexity and execution time. The
suitable neural architecture for on-line speed estimation is identified
and the promising results obtained are presented.
Abstract: This study was aimed to determine seasonal variations
of leaf nutrient concentrations to define nutrient needs related to
growing period and to compare irrigation programs in terms of
nutrient uptake. In this study,'Starkrimson Delicious' variety grafted
onto seedling rootstock was used during 2009-2010 growing seasons.
The study was conducted at E─ƒirdir Fruit Growing Research Station.
Leaf samples were taken in five different sample seasons (May, June,
July, August and September). Four different pan coefficients (0.50,
0.75, 1.0, 1.25) were applied during drip irrigation treatments in 7
days irrigation interval. Leaf K, Mg, Ca, P, Fe, Zn, Mn and Cu
concentrations were determined.
The results showed that among the seasonal changes, the highest
concentrations of K, Mg, P and Mn in leaves were recorded in May,
followed by a decrease in the other months, while in contrast Ca and
Fe showed the lowest concentration in May.
Results of the study demonstrate that among irrigation programs K
and Cu concentration in plants was significantly influenced. Cu
concentrations decreased with seasonal variations and different
irrigation programs. Thus, nutrient needs of 'Starkrimson Delicious'apple trees at different growth stages should be taken into
consideration before making effective fertilization program.
Abstract: Edge detection is usually the first step in medical
image processing. However, the difficulty increases when a
conventional kernel-based edge detector is applied to ultrasonic
images with a textural pattern and speckle noise. We designed an
adaptive diffusion filter to remove speckle noise while preserving the
initial edges detected by using a Sobel edge detector. We also propose
a genetic algorithm for edge selection to form complete boundaries of
the detected entities. We designed two fitness functions to evaluate
whether a criterion with a complex edge configuration can render a
better result than a simple criterion such as the strength of gradient.
The edges obtained by using a complex fitness function are thicker and
more fragmented than those obtained by using a simple fitness
function, suggesting that a complex edge selecting scheme is not
necessary for good edge detection in medical ultrasonic images;
instead, a proper noise-smoothing filter is the key.
Abstract: Fractal analyses of successive event of explosion
earthquake and harmonic tremor recorded at Semeru volcano were
carried out to investigate the dynamical system regarding to their
generating mechanism. The explosive eruptions accompanied by
explosion earthquakes and following volcanic tremor which are
generated by continuous emission of volcanic ash. The fractal
dimension of successive event of explosion and harmonic tremor was
estimated by Critical Exponent Method (CEM). It was found that the
method yield a higher fractal dimension of explosion earthquakes and
gradually decrease during the occurrence of harmonic tremor, and can
be considerably as correlated complexity of the source mechanism
from the variance of fractal dimension.
Abstract: Monitoring and control of cane sugar crystallization
processes depend on the stability of the supersaturation (σ ) state.
The most widely used information to represent σ is the electrical
conductivity κ of the solutions. Nevertheless, previous studies point
out the shortcomings of this approach: κ may be regarded as
inappropriate to guarantee an accurate estimation of σ in impure
solutions. To improve the process control efficiency, additional
information is necessary. The mass of crystals in the solution ( c m )
and the solubility (mass ratio of sugar to water / s w m m ) are relevant
to complete information. Indeed, c m inherently contains information
about the mass balance and / s w m m contains information about the
supersaturation state of the solution. The main problem is that c m
and / s w m m are not available on-line. In this paper, a model based
soft-sensor is presented for a final crystallization stage (C sugar).
Simulation results obtained on industrial data show the reliability of
this approach, c m and the crystal content ( cc ) being estimated with
a sufficient accuracy for achieving on-line monitoring in industry
Abstract: The next generation wireless systems, especially the
cognitive radio networks aim at utilizing network resources more
efficiently. They share a wide range of available spectrum in an
opportunistic manner. In this paper, we propose a quality
management model for short-term sub-lease of unutilized spectrum
bands to different service providers. We built our model on
competitive secondary market architecture. To establish the
necessary conditions for convergent behavior, we utilize techniques
from game theory. Our proposed model is based on potential game
approach that is suitable for systems with dynamic decision making.
The Nash equilibrium point tells the spectrum holders the ideal price
values where profit is maximized at the highest level of customer
satisfaction. Our numerical results show that the price decisions of
the network providers depend on the price and QoS of their own
bands as well as the prices and QoS levels of their opponents- bands.