Abstract: Saturated hydraulic conductivity is one of the soil
hydraulic properties which is widely used in environmental studies
especially subsurface ground water. Since, its direct measurement is
time consuming and therefore costly, indirect methods such as
pedotransfer functions have been developed based on multiple linear
regression equations and neural networks model in order to estimate
saturated hydraulic conductivity from readily available soil
properties e.g. sand, silt, and clay contents, bulk density, and organic
matter. The objective of this study was to develop neural networks
(NNs) model to estimate saturated hydraulic conductivity from
available parameters such as sand and clay contents, bulk density,
van Genuchten retention model parameters (i.e. r
θ , α , and n) as well
as effective porosity. We used two methods to calculate effective
porosity: : (1) eff s FC φ =θ -θ , and (2) inf φ =θ -θ eff s , in which s
θ is
saturated water content, FC θ is water content retained at -33 kPa
matric potential, and inf θ is water content at the inflection point.
Total of 311 soil samples from the UNSODA database was divided
into three groups as 187 for the training, 62 for the validation (to
avoid over training), and 62 for the test of NNs model. A commercial
neural network toolbox of MATLAB software with a multi-layer
perceptron model and back propagation algorithm were used for the
training procedure. The statistical parameters such as correlation
coefficient (R2), and mean square error (MSE) were also used to
evaluate the developed NNs model. The best number of neurons in
the middle layer of NNs model for methods (1) and (2) were
calculated 44 and 6, respectively. The R2 and MSE values of the test
phase were determined for method (1), 0.94 and 0.0016, and for
method (2), 0.98 and 0.00065, respectively, which shows that method
(2) estimates saturated hydraulic conductivity better than method (1).
Abstract: Application of Expert System in the area of agriculture would take the form of Integrated Crop Management decision aids and would encompass water management, fertilizer management, crop protection systems and identification of implements. In order to remain competitive, the modern farmer often relies on agricultural specialists and advisors to provide information for decision-making. An expert system normally composed of a knowledge base (information, heuristics, etc.), inference engine (analyzes knowledge base), and end user interface (accepting inputs, generating outputs). Software named 'CROP-9-DSS' incorporating all modern features like, graphics, photos, video clippings etc. has been developed. This package will aid as a decision support system for identification of pest and diseases with control measures, fertilizer recommendation system, water management system and identification of farm implements for leading crops of Kerala (India) namely Coconut, Rice, Cashew, Pepper, Banana, four vegetables like Amaranthus, Bhindi, Brinjal and Cucurbits. 'CROP-9-DSS' will act as an expert system to agricultural officers, scientists in the field of agriculture and extension workers for decision-making and help them in suggesting suitable recommendations.
Abstract: This study presents a simulation model for converting coal to methanol, based on gasification technology with the commercial chemical process simulator, Pro/II® V8.1.1. The methanol plant consists of air separation unit (ASU), gasification unit, gas clean-up unit, and methanol synthetic unit. The clean syngas is produced with the first three operating units, and the model has been verified with the reference data from United States Environment Protection Agency. The liquid phase methanol (LPMEOHTM) process is adopted in the methanol synthetic unit. Clean syngas goes through gas handing section to reach the reaction requirement, reactor loop/catalyst to generate methanol, and methanol distillation to get desired purity over 99.9 wt%. The ratio of the total energy combined with methanol and dimethyl ether to that of feed coal is 78.5% (gross efficiency). The net efficiency is 64.2% with the internal power consumption taken into account, based on the assumption that the efficiency of electricity generation is 40%.
Abstract: In this study, we sought to investigate the mercury
removal efficiency of manganese oxides from natural gas. The
fundamental studies on mercury removal with manganese oxides
sorbents were carried out in a laboratory scale fixed bed reactor at 30
°C with a mixture of methane (20%) and nitrogen gas laden with 4.8
ppb of elemental mercury. Manganese oxides with varying surface
area and crystalline phase were prepared by conventional precipitation
method in this study. The effects of surface area, crystallinity and
other metal oxides on mercury removal efficiency were investigated.
Effect of Ag impregnation on mercury removal efficiency was also
investigated. Ag supported on metal oxide such titania and zirconia as
reference materials were also used in this study for comparison. The
characteristics of mercury removal reaction with manganese oxide
was investigated using a temperature programmed desorption (TPD)
technique.
Manganese oxides showed very high Hg removal activity (about
73-93% Hg removal) for first time use. Surface area of the manganese
oxide samples decreased after heat-treatment and resulted in complete
loss of Hg removal ability for repeated use after Hg desorption in the
case of amorphous MnO2, and 75% loss of the initial Hg removal
activity for the crystalline MnO2. Mercury desorption efficiency of
crystalline MnO2 was very low (37%) for first time use and high (98%)
after second time use. Residual potassium content in MnO2 may have
some effect on the thermal stability of the adsorbed Hg species.
Desorption of Hg from manganese oxides occurs at much higher
temperatures (with a peak at 400 °C) than Ag/TiO2 or Ag/ZrO2.
Mercury may be captured on manganese oxides in the form of mercury
manganese oxide.
Abstract: Many multimedia communication applications require a
source to transmit messages to multiple destinations subject to quality
of service (QoS) delay constraint. To support delay constrained
multicast communications, computer networks need to guarantee an
upper bound end-to-end delay from the source node to each of
the destination nodes. This is known as multicast delay problem.
On the other hand, if the same message fails to arrive at each
destination node at the same time, there may arise inconsistency and
unfairness problem among users. This is related to multicast delayvariation
problem. The problem to find a minimum cost multicast
tree with delay and delay-variation constraints has been proven to
be NP-Complete. In this paper, we propose an efficient heuristic
algorithm, namely, Economic Delay and Delay-Variation Bounded
Multicast (EDVBM) algorithm, based on a novel heuristic function,
to construct an economic delay and delay-variation bounded multicast
tree. A noteworthy feature of this algorithm is that it has very high
probability of finding the optimal solution in polynomial time with
low computational complexity.
Abstract: In this paper, Economic Order Quantity (EOQ) based model for non-instantaneous Weibull distribution deteriorating items with power demand pattern is presented. In this model, the holding cost per unit of the item per unit time is assumed to be an increasing linear function of time spent in storage. Here the retailer is allowed a trade-credit offer by the supplier to buy more items. Also in this model, shortages are allowed and partially backlogged. The backlogging rate is dependent on the waiting time for the next replenishment. This model aids in minimizing the total inventory cost by finding the optimal time interval and finding the optimal order quantity. The optimal solution of the model is illustrated with the help of numerical examples. Finally sensitivity analysis and graphical representations are given to demonstrate the model.
Abstract: Visual attention allows user to select the most relevant
information to ongoing behaviour. This paper presents a study on; i)
the performance of people measurements, ii) accurateness of people
measurement of the peaks that correspond to chemical quantities
from the Magnetic Resonance Spectroscopy (MRS) graphs and iii)
affects of people measurements to the algorithm-based diagnosis.
Participant-s eye-movement was recorded using eye-tracker tool
(Eyelink II). This experiment involves three participants for
examining 20 MRS graphs to estimate the peaks of chemical
quantities which indicate the abnormalities associated with
Cerebellar Tumours (CT). The status of each MRS is verified by
using decision algorithm. Analysis involves determination of
humans-s eye movement pattern in measuring the peak of
spectrograms, scan path and determining the relationship of
distributions of fixation durations with the accuracy of measurement.
In particular, the eye-tracking data revealed which aspects of the
spectrogram received more visual attention and in what order they
were viewed. This preliminary investigation provides a proof of
concept for use of the eye tracking technology as the basis for
expanded CT diagnosis.
Abstract: A mathematical model based on a mass and energy
balance for the combustion in a cement rotary kiln was developed.
The model was used to investigate the impact of replacing about
45 % of the primary coal energy by different alternative fuels.
Refuse derived fuel, waste wood, solid hazardous waste and liquid
hazardous waste were used in the modeling. The results showed that
in order to keep the kiln temperature unchanged, and thereby
maintain the required clinker quality, the production capacity had to
be reduced by 1-15 %, depending on the fuel type. The reason for the
reduction is increased exhaust gas flow rates caused by the fuel
characteristics. The model, which has been successfully validated in a
full-scale experiment, was also used to show that the negative impact
on the production capacity can be avoided if a relatively small part of
the combustion air is replaced by pure oxygen.
Abstract: Markov games can be effectively used to design
controllers for nonlinear systems. The paper presents two novel
controller design algorithms by incorporating ideas from gametheory
literature that address safety and consistency issues of the
'learned' control strategy. A more widely used approach for
controller design is the H∞ optimal control, which suffers from high
computational demand and at times, may be infeasible. We generate
an optimal control policy for the agent (controller) via a simple
Linear Program enabling the controller to learn about the unknown
environment. The controller is facing an unknown environment and
in our formulation this environment corresponds to the behavior rules
of the noise modeled as the opponent. Proposed approaches aim to
achieve 'safe-consistent' and 'safe-universally consistent' controller
behavior by hybridizing 'min-max', 'fictitious play' and 'cautious
fictitious play' approaches drawn from game theory. We empirically
evaluate the approaches on a simulated Inverted Pendulum swing-up
task and compare its performance against standard Q learning.
Abstract: Waste problem is becoming a future problem all over the world. Magnesium wastes which can be used in recycling processes are produced by many industrial activities. Magnesium borates which have useful properties such as; high heat resistance, corrosion resistance, supermechanical strength, superinsulation, light weight, high coefficient of elasticity and so on. Addition, magnesium borates have great potential in the development of ceramic and detergents industry, whisker-reinforced composites, antiwear, and reducing friction additives.
In this study, using the starting materials of waste magnesium and H3BO3 the hydrothermal method was applied at a moderate temperature of 70oC with different reaction times. Several reaction times of waste magnesium to H3BO3 were selected as; 30, 60, 120, 240 minutes. After the synthesis, X-Ray Diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FT-IR) techniques were applied to products. As a result, the forms of Admontite [MgO(B2O3)3.7(H2O)] and Mcallisterite [Mg2(B6O7(OH)6)2.9(H2O)] were synthesized.
Abstract: Tea is a widely consumed beverage that contains many components. Caffeine belongs to this group of components called alkaloids contain nitrogen. In this study caffeine contents of three types of Turkish teas are determined by using extraction method. After condensation process, residue of caffeine and oil are obtained with evaporation. The oil which is in the residue is removed by hot water. Extraction process performed by using chloroform and the crude caffeine is obtained. From the results of experiments, caffeine contents are found in black tea, green tea and earl grey tea as 3.57±0.43%, 3.11±0.02%, 4.29±0.27%, respectively. Caffeine contents which are found in 1, 5 and 10 cups of tea are calculated. Furthermore, the daily intake of caffeine from black teas that affects human health is investigated.
Abstract: Variational methods for optical flow estimation are
known for their excellent performance. The method proposed by Brox
et al. [5] exemplifies the strength of that framework. It combines
several concepts into single energy functional that is then minimized
according to clear numerical procedure. In this paper we propose
a modification of that algorithm starting from the spatiotemporal
gradient constancy assumption. The numerical scheme allows to
establish the connection between our model and the CLG(H) method
introduced in [18]. Experimental evaluation carried out on synthetic
sequences shows the significant superiority of the spatial variant of
the proposed method. The comparison between methods for the realworld
sequence is also enclosed.
Abstract: The objectives of the study are to examine the
determinants of ERP implementation success factors of ERP
implementation. The result indicates that large scale ERP
implementation success consist of eight factors: project management
competence, knowledge sharing, ERP system quality , understanding,
user involvement, business process re-engineering, top management
support, organization readiness.
Abstract: The main goal of this seminal paper is to introduce the
application of Wireless Sensor Networks (WSN) in long distance
infrastructure monitoring (in particular in pipeline infrastructure
monitoring) – one of the on-going research projects by the Wireless
Communication Research Group at the department of Electronic and
Computer Engineering, Nnamdi Azikiwe University, Awka. The
current sensor network architectures for monitoring long distance
pipeline infrastructures are previewed. These are wired sensor
networks, RF wireless sensor networks, integrated wired and wireless
sensor networks. The reliability of these architectures is discussed.
Three reliability factors are used to compare the architectures in
terms of network connectivity, continuity of power supply for the
network, and the maintainability of the network. The constraints and
challenges of wireless sensor networks for monitoring and protecting
long distance pipeline infrastructure are discussed.
Abstract: A parametric study of a mixed-compression
supersonic inlet is performed and reported. The effects of inlet Mach
Numbers, varying from 4 to 10, and angle of attack, varying from 0
to 10, are reported for a constant inlet dynamic pressure. The paper
looked at the variations of mass flow rates through the inlet, gain in
entropy through the inlet, and the angles of the external oblique
shocks. The mass flow rates were found to decrease monotonically
with Mach numbers and increase with angle of attacks. On the other
hand the entropy gain through the inlet increased with increasing
Mach number and angle of attack. The variation in static pressure
was found to be identical from the inlet throat to the exit for Mach
number values higher than 6.
Abstract: The way music is interpreted by the human brain is a very interesting topic, but also an intricate one. Although this domain has been studied for over a century, many gray areas remain in the understanding of music. Recent advances have enabled us to perform accurate measurements of the time taken by the human brain to interpret and assimilate a sound. Cognitive computing provides tools and development environments that facilitate human cognition simulation. ACT-R is a cognitive architecture which offers an environment for implementing human cognitive tasks. This project combines our understanding of the music interpretation by a human listener and the ACT-R cognitive architecture to build SINGER, a computerized simulation for listening and recalling songs. The results are similar to human experimental data. Simulation results also show how it is easier to remember short melodies than long melodies which require more trials to be recalled correctly.
Abstract: This work presents a methodology for the design and
manufacture of propellers oriented to the experimental verification of
theoretical results based on the combined model. The design process
begins by using algorithms in Matlab which output data contain the
coordinates of the points that define the blade airfoils, in this case the
NACA 6512 airfoil was used. The modeling for the propeller blade
was made in NX7, through the imported files in Matlab and with the
help of surfaces. Later, the hub and the clamps were also modeled.
Finally, NX 7 also made possible to create post-processed files to the
required machine. It is possible to find the block of numbers with G
& M codes about the type of driver on the machine. The file
extension is .ptp. These files made possible to manufacture the blade,
and the hub of the propeller.
Abstract: A strategy is implemented to find the improved configuration design of an existing aircraft structure by executing topology and shape optimizations. Structural analysis of the Initial Design Space is performed in ANSYS under the loads pertinent to operating and ground conditions. By using the FEA results and data, an initial optimized layout configuration is attained by exploiting nonparametric topology optimization in TOSCA software. Topological optimized surfaces are then smoothened and imported in ANSYS to develop the geometrical features. Nodes at the critical locations of resulting voids are selected for sketching rough profiles. Rough profiles are further refined and CAD feasible geometric features are generated. The modified model is then analyzed under the same loadings and constraints as defined for topology optimization. Shape at the peak stress concentration areas are further optimized by exploiting the shape optimization in TOSCA.shape module. The harmonized stressed model with the modified surfaces is then imported in CATIA to develop the final design.
Abstract: The concept of e-government has begun to spread among countries. It is based on the use of information communication technology (ICT) to fully utilize government resources, as well as to provide government services to citizens, investors and foreigners. Critical factors are the factors that are determined by the senior management of each organization; the success or failure of the organization depends on the effective implementation of critical factors. These factors vary from one organization to another according to their activity, size and functions. It is very important that organizations identify them in order to avoid the risk of implementing initiatives that may fail to work, while simultaneously exploiting opportunities that may succeed in working. The main focus of this paper is to investigate the majority of critical success factors (CSFs) associated with the implementation of e-government projects. This study concentrates on both technical and nontechnical factors. This paper concludes by listing the majority of CSFs relating to successful e-government implementation in Bahrain.
Abstract: A strip domain decomposition parallel algorithm for fast direct Poisson solver is presented on a 3D Cartesian staggered grid. The parallel algorithm follows the principles of sequential algorithm for fast direct Poisson solver. Both Dirichlet and Neumann boundary conditions are addressed. Several test cases are likewise addressed in order to shed light on accuracy and efficiency in the strip domain parallelization algorithm. Actually the current implementation shows a very high efficiency when dealing with a large grid mesh up to 3.6 * 109 under massive parallel approach, which explicitly demonstrates that the proposed algorithm is ready for massive parallel computing.