Abstract: Field experiments were carried out at Owo, southwest Nigeria to evaluate the effect of different tillage practices (zero tillage with mulch (ZTM), row tillage (RT) and conventional tillage (CT), and with or without oil palm bunch ash plus poultry manure (OBA+PM) on soil chemical properties, growth and yield of ginger. The experiment was laid out in a randomized complete plot design with three replications. Soil chemical properties, growth and fresh rhizome yield reduced with frequency/intensity of tillage imposed while application of OBA+PM increased them. Among the tillage practices, the highest fresh rhizome yield (15.0t ha-1) was produced by ZTM which was significantly different from other tillage practices. Among the tillage – OBA+PM combinations, the most satisfactorily yield (20.1t ha-1) was produced by ZTM+OBA+PM while the lowest yield (15.7t ha-1) was in CT+OBA+PM.
Abstract: In this study, a mathematical model was proposed and
the accuracy of this model was assessed to predict the growth of
Pseudomonas aeruginosa and rhamnolipid production under nitrogen
limiting (sodium nitrate) fed-batch fermentation. All of the
parameters used in this model were achieved individually without
using any data from the literature.
The overall growth kinetic of the strain was evaluated using a
dual-parallel substrate Monod equation which was described by
several batch experimental data. Fed-batch data under different
glycerol (as the sole carbon source, C/N=10) concentrations and feed
flow rates were used to describe the proposed fed-batch model and
other parameters. In order to verify the accuracy of the proposed
model several verification experiments were performed in a vast
range of initial glycerol concentrations. While the results showed an
acceptable prediction for rhamnolipid production (less than 10%
error), in case of biomass prediction the errors were less than 23%. It
was also found that the rhamnolipid production by P. aeruginosa was
more sensitive at low glycerol concentrations.
Based on the findings of this work, it was concluded that the
proposed model could effectively be employed for rhamnolipid
production by this strain under fed-batch fermentation on up to 80 g l-
1 glycerol.
Abstract: In this project cadmium ions were adsorbed from
aqueous solutions onto either date pits; a cheap agricultural and nontoxic
material, or chemically activated carbon prepared from date pits
using phosphoric acid. A series of experiments were conducted in a
batch adsorption technique to assess the feasibility of using the
prepared adsorbents. The effects of the process variables such as
initial cadmium ions concentration, contact time, solution pH and
adsorbent dose on the adsorption capacity of both adsorbents were
studied. The experimental data were tested using different isotherm
models such as Langmuir, Freundlich, Tempkin and Dubinin-
Radushkevich. The results showed that although the equilibrium data
could be described by all models used, Langmuir model gave slightly
better results when using activated carbon while Freundlich model,
gave better results with date pits.
Abstract: Polyphenolics and sugar are the components of many
fruit juices. In this work, the performance of ultra-filtration (UF) for
separating phenolic compounds from apple juice was studied by
performing batch experiments in a membrane module with an area of
0.1 m2 and fitted with a regenerated cellulose membrane of 1 kDa
MWCO. The effects of various operating conditions: transmembrane
pressure (3, 4, 5 bar), temperature (30, 35, 40 ºC), pH (2, 3, 4, 5),
feed concentration (3, 5, 7, 10, 15 ºBrix for apple juice) and feed flow
rate (1, 1.5, 1.8 L/min) on the performance were determined.
The optimum operating conditions were: transmembrane pressure
4 bar, temperature 30 ºC, feed flow rate 1 – 1.8 L/min, pH 3 and 10
Brix (apple juice). After performing ultrafiltration under these
conditions, the concentration of polyphenolics in retentate was
increased by a factor of up to 2.7 with up to 70% recovered in the
permeate and with approx. 20% of the sugar in that stream..
Application of diafiltration (addition of water to the concentrate) can
regain the flux by a factor of 1.5, which has been decreased due to
fouling. The material balance performed on the process has shown
the amount of deposits on the membrane and the extent of fouling in
the system. In conclusion, ultrafiltration has been demonstrated as a
potential technology to separate the polyphenolics and sugars from
their mixtures and can be applied to remove sugars from fruit juice.
Abstract: When a high DC voltage is applied to a capacitor with
strongly asymmetrical electrodes, it generates a mechanical force that
affects the whole capacitor. This phenomenon is most likely to be
caused by the motion of ions generated around the smaller of the two
electrodes and their subsequent interaction with the surrounding
medium. A method to measure this force has been devised and used.
A formula describing the force has also been derived. After
comparing the data gained through experiments with those acquired
using the theoretical formula, a difference was found above a certain
value of current. This paper also gives reasons for this difference.
Abstract: AAM (active appearance model) has been successfully
applied to face and facial feature localization. However, its performance is sensitive to initial parameter values. In this paper, we propose a two-stage AAM for robust face alignment, which first fits an
inner face-AAM model to the inner facial feature points of the face and then localizes the whole face and facial features by optimizing the
whole face-AAM model parameters. Experiments show that the proposed face alignment method using two-stage AAM is more reliable to the background and the head pose than the standard
AAM-based face alignment method.
Abstract: In online context, the design and implementation of
effective remote laboratories environment is highly challenging on
account of hardware and software needs. This paper presents the
remote laboratory software framework modified from ilab shared
architecture (ISA). The ISA is a framework which enables students to
remotely acccess and control experimental hardware using internet
infrastructure. The need for remote laboratories came after
experiencing problems imposed by traditional laboratories. Among
them are: the high cost of laboratory equipment, scarcity of space,
scarcity of technical personnel along with the restricted university
budget creates a significant bottleneck on building required
laboratory experiments. The solution to these problems is to build
web-accessible laboratories. Remote laboratories allow students and
educators to interact with real laboratory equipment located
anywhere in the world at anytime. Recently, many universities and
other educational institutions especially in third world countries rely
on simulations because they do not afford the experimental
equipment they require to their students. Remote laboratories enable
users to get real data from real-time hand-on experiments. To
implement many remote laboratories, the system architecture should
be flexible, understandable and easy to implement, so that different
laboratories with different hardware can be deployed easily. The
modifications were made to enable developers to add more
equipment in ISA framework and to attract the new developers to
develop many online laboratories.
Abstract: A new approach to promote the generalization ability
of neural networks is presented. It is based on the point of view of
fuzzy theory. This approach is implemented through shrinking or
magnifying the input vector, thereby reducing the difference between
training set and testing set. It is called “shrinking-magnifying
approach" (SMA). At the same time, a new algorithm; α-algorithm is
presented to find out the appropriate shrinking-magnifying-factor
(SMF) α and obtain better generalization ability of neural networks.
Quite a few simulation experiments serve to study the effect of SMA
and α-algorithm. The experiment results are discussed in detail, and
the function principle of SMA is analyzed in theory. The results of
experiments and analyses show that the new approach is not only
simpler and easier, but also is very effective to many neural networks
and many classification problems. In our experiments, the proportions
promoting the generalization ability of neural networks have even
reached 90%.
Abstract: Simulations play a major role in education not only because they provide realistic models with which students can interact to acquire real world experiences, but also because they constitute safe environments in which students can repeat processes without any risk in order to perceive easier concepts and theories. Virtual reality is widely recognized as a significant technological advance that can facilitate learning process through the development of highly realistic 3D simulations supporting immersive and interactive features. The objective of this paper is to analyze the influence of virtual reality-s use in chemistry instruction as well as to present an integrated web-based learning environment for the simulation of chemical experiments. The proposed application constitutes a cost-effective solution for both schools and universities without appropriate infrastructure and a valuable tool for distance learning and life-long education in chemistry. Its educational objectives are the familiarization of students with the equipment of a real chemical laboratory and the execution of virtual volumetric analysis experiments with the active participation of students.
Abstract: In order to meet environmental norms, Indian fuel
policy aims at producing ultra low sulphur diesel (ULSD) in near
future. A catalyst for meeting such requirements has been developed
and kinetics of this catalytic process is being looked into. In the
present investigations, effect of mass transfer on kinetics of ultra deep
hydrodesulphurization (UDHDS) to produce ULSD has been studied
to determine intrinsic kinetics over a pre-sulphided catalyst.
Experiments have been carried out in a continuous flow micro reactor
operated in the temperature range of 330 to 3600C, whsv of 1 hr-1 at a
pressure of 35 bar, and its parameters estimated. Based on the derived
rate expression and estimated parameters optimum operation range
has been determined for this UDHDS catalyst to obtain ULSD
product.
Abstract: Principle component analysis is often combined with
the state-of-art classification algorithms to recognize human faces.
However, principle component analysis can only capture these
features contributing to the global characteristics of data because it is a
global feature selection algorithm. It misses those features
contributing to the local characteristics of data because each principal
component only contains some levels of global characteristics of data.
In this study, we present a novel face recognition approach using
non-negative principal component analysis which is added with the
constraint of non-negative to improve data locality and contribute to
elucidating latent data structures. Experiments are performed on the
Cambridge ORL face database. We demonstrate the strong
performances of the algorithm in recognizing human faces in
comparison with PCA and NREMF approaches.
Abstract: In the present paper, the three-dimensional
temperature field of tool is determined during the machining and
compared with experimental work on C45 workpiece using carbide
cutting tool inserts. During the metal cutting operations, high
temperature is generated in the tool cutting edge which influence on
the rate of tool wear. Temperature is most important characteristic of
machining processes; since many parameters such as cutting speed,
surface quality and cutting forces depend on the temperature and high
temperatures can cause high mechanical stresses which lead to early
tool wear and reduce tool life. Therefore, considerable attention is
paid to determine tool temperatures. The experiments are carried out
for dry and orthogonal machining condition. The results show that
the increase of tool temperature depends on depth of cut and
especially cutting speed in high range of cutting conditions.
Abstract: This paper proposes an efficient learning method for the layered neural networks based on the selection of training data and input characteristics of an output layer unit. Comparing to recent neural networks; pulse neural networks, quantum neuro computation, etc, the multilayer network is widely used due to its simple structure. When learning objects are complicated, the problems, such as unsuccessful learning or a significant time required in learning, remain unsolved. Focusing on the input data during the learning stage, we undertook an experiment to identify the data that makes large errors and interferes with the learning process. Our method devides the learning process into several stages. In general, input characteristics to an output layer unit show oscillation during learning process for complicated problems. The multi-stage learning method proposes by the authors for the function approximation problems of classifying learning data in a phased manner, focusing on their learnabilities prior to learning in the multi layered neural network, and demonstrates validity of the multi-stage learning method. Specifically, this paper verifies by computer experiments that both of learning accuracy and learning time are improved of the BP method as a learning rule of the multi-stage learning method. In learning, oscillatory phenomena of a learning curve serve an important role in learning performance. The authors also discuss the occurrence mechanisms of oscillatory phenomena in learning. Furthermore, the authors discuss the reasons that errors of some data remain large value even after learning, observing behaviors during learning.
Abstract: The main objectives of this paper are to measure
pollutants concentrations in the oil refinery area in Kuwait over three
periods during one year, obtain recent emission inventory for the
three refineries of Kuwait, use AERMOD and the emission inventory
to predict pollutants concentrations and distribution, compare model
predictions against measured data, and perform numerical
experiments to determine conditions at which emission rates and the
resulting pollutant dispersion is below maximum allowable limits.
Abstract: Granular computing deals with representation of information in the form of some aggregates and related methods for transformation and analysis for problem solving. A granulation scheme based on clustering and Rough Set Theory is presented with focus on structured conceptualization of information has been presented in this paper. Experiments for the proposed method on four labeled data exhibit good result with reference to classification problem. The proposed granulation technique is semi-supervised imbibing global as well as local information granulation. To represent the results of the attribute oriented granulation a tree structure is proposed in this paper.
Abstract: Segmentation in ultrasound images is challenging due to the interference from speckle noise and fuzziness of boundaries. In this paper, a segmentation scheme using fuzzy c-means (FCM) clustering incorporating both intensity and texture information of images is proposed to extract breast lesions in ultrasound images. Firstly, the nonlinear structure tensor, which can facilitate to refine the edges detected by intensity, is used to extract speckle texture. And then, a spatial FCM clustering is applied on the image feature space for segmentation. In the experiments with simulated and clinical ultrasound images, the spatial FCM clustering with both intensity and texture information gets more accurate results than the conventional FCM or spatial FCM without texture information.
Abstract: SAD (Sum of Absolute Difference) algorithm is
heavily used in motion estimation which is computationally highly
demanding process in motion picture encoding. To enhance the
performance of motion picture encoding on a VLIW processor, an
efficient implementation of SAD algorithm on the VLIW processor is
essential. SAD algorithm is programmed as a nested loop with a
conditional branch. In VLIW processors, loop is usually optimized by
software pipelining, but researches on optimal scheduling of software
pipelining for nested loops, especially nested loops with conditional
branches are rare. In this paper, we propose an optimal scheduling and
implementation of SAD algorithm with conditional branch on a VLIW
DSP processor. The proposed optimal scheduling first transforms the
nested loop with conditional branch into a single loop with conditional
branch with consideration of full utilization of ILP capability of the
VLIW processor and realization of earlier escape from the loop. Next,
the proposed optimal scheduling applies a modulo scheduling
technique developed for single loop. Based on this optimal scheduling
strategy, optimal implementation of SAD algorithm on TMS320C67x,
a VLIW DSP is presented. Through experiments on TMS320C6713
DSK, it is shown that H.263 encoder with the proposed SAD
implementation performs better than other H.263 encoder with other
SAD implementations, and that the code size of the optimal SAD
implementation is small enough to be appropriate for embedded
environments.
Abstract: Camera calibration plays an important role in the domain of the analysis of sports video. Considering soccer video, in most cases, the cross-points can be used for calibration at the center of the soccer field are not sufficient, so this paper introduces a new automatic camera calibration algorithm focus on solving this problem by using the properties of images of the center circle, halfway line and a touch line. After the theoretical analysis, a practicable automatic algorithm is proposed. Very little information used though, results of experiments with both synthetic data and real data show that the algorithm is applicable.
Abstract: With the aim of improving nutritional profile and antioxidant capacity of gluten-free cookies, blueberry pomace, by-product of juice production, was processed into a new food ingredient by drying and grinding and used for a gluten-free cookie formulation. Since the quality of a baked product is highly influenced by the baking conditions, the objective of this work was to optimize the baking time and thickness of dough pieces, by applying Response Surface Methodology (RSM) in order to obtain the best technological quality of the cookies. The experiments were carried out according to a Central Composite Design (CCD) by selecting the dough thickness and baking time as independent variables, while hardness, color parameters (L*, a* and b* values), water activity, diameter and short/long ratio were response variables. According to the results of RSM analysis, the baking time of 13.74min and dough thickness of 4.08mm was found to be the optimal for the baking temperature of 170°C. As similar optimal parameters were obtained by previously conducted experiment based on sensory analysis, response surface methodology (RSM) can be considered as a suitable approach to optimize the baking process.
Abstract: For the past one decade, biclustering has become popular data mining technique not only in the field of biological data analysis but also in other applications like text mining, market data analysis with high-dimensional two-way datasets. Biclustering clusters both rows and columns of a dataset simultaneously, as opposed to traditional clustering which clusters either rows or columns of a dataset. It retrieves subgroups of objects that are similar in one subgroup of variables and different in the remaining variables. Firefly Algorithm (FA) is a recently-proposed metaheuristic inspired by the collective behavior of fireflies. This paper provides a preliminary assessment of discrete version of FA (DFA) while coping with the task of mining coherent and large volume bicluster from web usage dataset. The experiments were conducted on two web usage datasets from public dataset repository whereby the performance of FA was compared with that exhibited by other population-based metaheuristic called binary Particle Swarm Optimization (PSO). The results achieved demonstrate the usefulness of DFA while tackling the biclustering problem.