Abstract: The paper depicts air velocity values, reproduced by laser Doppler anemometer (LDA) and ultrasonic anemometer (UA), relations with calculated ones from flow rate measurements using the gas meter which calibration uncertainty is ± (0.15 – 0.30) %. Investigation had been performed in channel installed in aerodynamical facility used as a part of national standard of air velocity. Relations defined in a research let us confirm the LDA and UA for air velocity reproduction to be the most advantageous measures. The results affirm ultrasonic anemometer to be reliable and favourable instrument for measurement of mean velocity or control of velocity stability in the velocity range of 0.05 m/s – 10 (15) m/s when the LDA used. The main aim of this research is to investigate low velocity regularities, starting from 0.05 m/s, including region of turbulent, laminar and transitional air flows. Theoretical and experimental results and brief analysis of it are given in the paper. Maximum and mean velocity relations for transitional air flow having unique distribution are represented. Transitional flow having distinctive and different from laminar and turbulent flow characteristics experimentally have not yet been analysed.
Abstract: Hemorrhage Disease of Grass Carp (HDGC) is a kind
of commonly occurring illnesses in summer, and the extremely high
death rate result in colossal losses to aquaculture. As the complex
connections among each factor which influences aquiculture diseases,
there-s no quit reasonable mathematical model to solve the problem at
present.A BP neural network which with excellent nonlinear mapping
coherence was adopted to establish mathematical model;
Environmental factor, which can easily detected, such as breeding
density, water temperature, pH and light intensity was set as the main
analyzing object. 25 groups of experimental data were used for
training and test, and the accuracy of using the model to predict the
trend of HDGC was above 80%. It is demonstrated that BP neural
network for predicating diseases in HDGC has a particularly
objectivity and practicality, thus it can be spread to other aquiculture
disease.
Abstract: This experiment was carried out to study the effect of
AMF, drought stress and phosphorus on physiological growth indices of basil at Iran using by a split-plot design with three replications.
The main-plot factor included: two levels of irrigation regimes (control=no drought stress and irrigation after 80 evaporation=
drought stress condition) while the sub-plot factors included
phosphorus (0, 35 and 70 kg/ha) and application and non-application of Glomus fasciculatum. The results showed that total dry matter
(TDM), life area index (LAI), relative growth rate (RGR) and crop growth rate (CGR) were all highly significantly different among the
phosphorus, whereas drought stress had effect of practical
significance on TDM, LAI, RGR and CGR. The results also showed that the highest TDM, LAI, RGR and CGR were obtained from
application of Glomus fasciculatum under no-drought condition.
Abstract: In this study, the effects of machining parameters on
specific energy during surface grinding of 6061Al-SiC35P
composites are investigated. Vol% of SiC, feed and depth of cut were
chosen as process variables. The power needed for the calculation of
the specific energy is measured from the two watt meter method.
Experiments are conducted using standard RSM design called Central
composite design (CCD). A second order response surface model was
developed for specific energy. The results identify the significant
influence factors to minimize the specific energy. The confirmation
results demonstrate the practicability and effectiveness of the
proposed approach.
Abstract: Nanoemulsions are a class of emulsions with a droplet
size in the range of 50–500 nm and have attracted a great deal of
attention in recent years because it is unique characteristics. The
physicochemical properties of nanoemulsion suggests that it can be
successfully used to recover the residual oil which is trapped in the
fine pore of reservoir rock by capillary forces after primary and
secondary recovery. Oil-in-water nanoemulsion which can be formed
by high-energy emulsification techniques using specific surfactants
can reduce oil-water interfacial tension (IFT) by 3-4 orders of
magnitude. The present work is aimed on characterization of oil-inwater
nanoemulsion in terms of its phase behavior, morphological
studies; interfacial energy; ability to reduce the interfacial tension and
understanding the mechanisms of mobilization and displacement of
entrapped oil blobs by lowering interfacial tension both at the
macroscopic and microscopic level. In order to investigate the
efficiency of oil-water nanoemulsion in enhanced oil recovery
(EOR), experiments were performed to characterize the emulsion in
terms of their physicochemical properties and size distribution of the
dispersed oil droplet in water phase. Synthetic mineral oil and a series
of surfactants were used to prepare oil-in-water emulsions.
Characterization of emulsion shows that it follows pseudo-plastic
behaviour and drop size of dispersed oil phase follows lognormal
distribution. Flooding experiments were also carried out in a
sandpack system to evaluate the effectiveness of the nanoemulsion as
displacing fluid for enhanced oil recovery. Substantial additional
recoveries (more than 25% of original oil in place) over conventional
water flooding were obtained in the present investigation.
Abstract: Automated discovery of hierarchical structures in
large data sets has been an active research area in the recent past.
This paper focuses on the issue of mining generalized rules with crisp
hierarchical structure using Genetic Programming (GP) approach to
knowledge discovery. The post-processing scheme presented in this
work uses flat rules as initial individuals of GP and discovers
hierarchical structure. Suitable genetic operators are proposed for the
suggested encoding. Based on the Subsumption Matrix(SM), an
appropriate fitness function is suggested. Finally, Hierarchical
Production Rules (HPRs) are generated from the discovered
hierarchy. Experimental results are presented to demonstrate the
performance of the proposed algorithm.
Abstract: Digital news with a variety topics is abundant on the
internet. The problem is to classify news based on its appropriate
category to facilitate user to find relevant news rapidly. Classifier
engine is used to split any news automatically into the respective
category. This research employs Support Vector Machine (SVM) to
classify Indonesian news. SVM is a robust method to classify
binary classes. The core processing of SVM is in the formation of an
optimum separating plane to separate the different classes. For
multiclass problem, a mechanism called one against one is used to
combine the binary classification result. Documents were taken
from the Indonesian digital news site, www.kompas.com. The
experiment showed a promising result with the accuracy rate of 85%.
This system is feasible to be implemented on Indonesian news
classification.
Abstract: In the study of honeycomb crushing under quasistatic loading, two parameters are important, the mean crushing stress and the wavelength of the folding mode. The previous theoretical models did not consider the true cylindrical curvature effects and the flow stress in the folding mode of honeycomb material. The present paper introduces a modification on Wierzbicki-s model based on considering two above mentioned parameters in estimating the mean crushing stress and the wavelength through implementation of the energy method. Comparison of the results obtained by the new model and Wierzbicki-s model with existing experimental data shows better prediction by the model presented in this paper.
Abstract: The study of proteomics reached unexpected levels of
interest, as a direct consequence of its discovered influence over
some complex biological phenomena, such as problematic diseases
like cancer. This paper presents a new technique that allows for an
accurate analysis of the human interactome network. It is basically
a two-step analysis process that involves, at first, the detection of
each protein-s absolute importance through the betweenness centrality
computation. Then, the second step determines the functionallyrelated
communities of proteins. For this purpose, we use a community
detection technique that is based on the edge betweenness
calculation. The new technique was thoroughly tested on real biological
data and the results prove some interesting properties of those proteins that are involved in the carcinogenesis process. Apart from its
experimental usefulness, the novel technique is also computationally
effective in terms of execution times. Based on the analysis- results, some topological features of cancer mutated proteins are presented
and a possible optimization solution for cancer drugs design is suggested.
Abstract: In this paper we present a modification to existed model of threshold for shot cut detection, which is able to adapt itself to the sequence statistics and operate in real time, because it use for calculation only previously evaluated frames. The efficiency of proposed modified adaptive threshold scheme was verified through extensive test experiment with several similarity metrics and achieved results were compared to the results reached by the original model. According to results proposed threshold scheme reached higher accuracy than existed original model.
Abstract: A computational platform is presented in this
contribution. It has been designed as a virtual laboratory to be used
for exploring optimization algorithms in biological problems. This
platform is built on a blackboard-based agent architecture. As a test
case, the version of the platform presented here is devoted to the
study of protein folding, initially with a bead-like description of the
chain and with the widely used model of hydrophobic and polar
residues (HP model). Some details of the platform design are
presented along with its capabilities and also are revised some
explorations of the protein folding problems with different types of
discrete space. It is also shown the capability of the platform to
incorporate specific tools for the structural analysis of the runs in
order to understand and improve the optimization process.
Accordingly, the results obtained demonstrate that the ensemble of
computational tools into a single platform is worthwhile by itself,
since experiments developed on it can be designed to fulfill different
levels of information in a self-consistent fashion. By now, it is being
explored how an experiment design can be useful to create a
computational agent to be included within the platform. These
inclusions of designed agents –or software pieces– are useful for the
better accomplishment of the tasks to be developed by the platform.
Clearly, while the number of agents increases the new version of the
virtual laboratory thus enhances in robustness and functionality.
Abstract: There are two common types of operational research techniques, optimisation and metaheuristic methods. The latter may be defined as a sequential process that intelligently performs the exploration and exploitation adopted by natural intelligence and strong inspiration to form several iterative searches. An aim is to effectively determine near optimal solutions in a solution space. In this work, a type of metaheuristics called Ant Colonies Optimisation, ACO, inspired by a foraging behaviour of ants was adapted to find optimal solutions of eight non-linear continuous mathematical models. Under a consideration of a solution space in a specified region on each model, sub-solutions may contain global or multiple local optimum. Moreover, the algorithm has several common parameters; number of ants, moves, and iterations, which act as the algorithm-s driver. A series of computational experiments for initialising parameters were conducted through methods of Rigid Simplex, RS, and Modified Simplex, MSM. Experimental results were analysed in terms of the best so far solutions, mean and standard deviation. Finally, they stated a recommendation of proper level settings of ACO parameters for all eight functions. These parameter settings can be applied as a guideline for future uses of ACO. This is to promote an ease of use of ACO in real industrial processes. It was found that the results obtained from MSM were pretty similar to those gained from RS. However, if these results with noise standard deviations of 1 and 3 are compared, MSM will reach optimal solutions more efficiently than RS, in terms of speed of convergence.
Abstract: In this paper, a novel copyright protection scheme for digital images based on Visual Cryptography and Statistics is proposed. In our scheme, the theories and properties of sampling distribution of means and visual cryptography are employed to achieve the requirements of robustness and security. Our method does not need to alter the original image and can identify the ownership without resorting to the original image. Besides, our method allows multiple watermarks to be registered for a single host image without causing any damage to other hidden watermarks. Moreover, it is also possible for our scheme to cast a larger watermark into a smaller host image. Finally, experimental results will show the robustness of our scheme against several common attacks.
Abstract: An upwind difference approximation is used for a singularly perturbed problem in material science. Based on the discrete Green-s function theory, the error estimate in maximum norm is achieved, which is first-order uniformly convergent with respect to the perturbation parameter. The numerical experimental result is verified the valid of the theoretical analysis.
Abstract: This work involved the use of phytoremediation to
remediate an aged soil contaminated with polychlorinated biphenyls
(PCBs). At microcosm scale, tests were prepared using soil samples
that have been collected in an industrial area with a total PCBs
concentration of about 250 μg kg-1. Medicago sativa and Lolium
italicum were the species selected in this study that is used as
“feasibility test" for full scale remediation. The experiment was
carried out with the addition of a mixture of randomly methylatedbeta-
cyclodextrins (RAMEB). At the end of the experiment analysis
of soil samples showed that in general the presence of plants has led
to a higher degradation of most congeners with respect to not
vegetated soil. The two plant species efficiencies were comparable
and improved by RAMEB addition with a final reduction of total
PCBs near to 50%. With increasing the chlorination of the congeners
the removal percentage of PCBs progressively decreased.
Abstract: The present experimental investigation brings about
a comparative study of lactic acid production by pure strains of
Lactobacilli (1) L. delbreuckii (NCIM2025), (2) L. pentosus (NCIM
2912), (3) Lactobacillus sp.(NCIM 2734, (4) Lactobacillus sp.
(NCIM2084) and coculture of strain-1 and Stain-2 in solid bed of
wheat bran, under the influence of different nitrogen sources such as
baker-s yeast, meat extract and proteose peptone. Among the pure
cultures, strain-3 attained lowest pH value of 3.44, hence highest acid
formation 46.41 g/L, while the coculture attained an overall
maximum value 47.56 g/L lactic acid (pH 3.38) at 15 g/L and 20 g/L
level of baker-s yeast, respectively.
Abstract: We report the electronic structure and optical
properties of NdF3 compound. Our calculations are based on density
functional theory (DFT) using the full potential linearized augmented
plane wave (FPLAPW) method with the inclusion of spin orbit
coupling. We employed the local spin density approximation (LSDA)
and Coulomb-corrected local spin density approximation, known for
treating the highly correlated 4f electrons properly, is able to
reproduce the correct insulating ground state. We find that the
standard LSDA approach is incapable of correctly describing the
electronic properties of such materials since it positions the f-bands
incorrectly resulting in an incorrect metallic ground state. On the
other hand, LSDA + U approximation, known for treating the highly
correlated 4f electrons properly, is able to reproduce the correct
insulating ground state. Interestingly, however, we do not find any
significant differences in the optical properties calculated using
LSDA, and LSDA + U suggesting that the 4f electrons do not play a
decisive role in the optical properties of these compounds. The
reflectivity for NdF3 compound stays low till 7 eV which is
consistent with their large energy gaps. The calculated energy gaps
are in good agreement with experiments. Our calculated reflectivity
compares well with the experimental data and the results are analyzed
in the light of band to band transitions.
Abstract: In most rule-induction algorithms, the only operator used against nominal attributes is the equality operator =. In this paper, we first propose the use of the inequality operator, ≠, in addition to the equality operator, to increase the expressiveness of induced rules. Then, we present a new method, Binary Coding, which can be used along with an arbitrary rule-induction algorithm to make use of the inequality operator without any need to change the algorithm. Experimental results suggest that the Binary Coding method is promising enough for further investigation, especially in cases where the minimum number of rules is desirable.
Abstract: Keystroke authentication is a new access control system
to identify legitimate users via their typing behavior. In this paper,
machine learning techniques are adapted for keystroke authentication.
Seven learning methods are used to build models to differentiate user
keystroke patterns. The selected classification methods are Decision
Tree, Naive Bayesian, Instance Based Learning, Decision Table, One
Rule, Random Tree and K-star. Among these methods, three of them
are studied in more details. The results show that machine learning
is a feasible alternative for keystroke authentication. Compared to
the conventional Nearest Neighbour method in the recent research,
learning methods especially Decision Tree can be more accurate. In
addition, the experiment results reveal that 3-Grams is more accurate
than 2-Grams and 4-Grams for feature extraction. Also, combination
of attributes tend to result higher accuracy.
Abstract: In this paper, the effect of bolt clamping force on the fatigue behavior of bolted single lap joints of aluminum alloy 2024- T3 have been studied using numerical finite element method. To do so, a three dimensional model according to the bolted single lap joint has been created and numerical analysis has been carried out using finite element based package. Then the stress distribution and also the slip amplitudes have been calculated in the critical regions and the outcome have been compared with the available experimental fatigue tests results. The numerical results show that in low applied clamping force, the fatigue failure of the specimens occur around the stress concentration location (the bolted hole edge) due to the tensile stresses and thus fatigue crack propagation, but with increase of the clamping force, the fatigue life increases and the cracks nucleate and propagate far from the hole edge because of fretting fatigue. In other words, with the further increase of clamping force value of the joint, the fatigue life reduces due to occurrence of the fretting fatigue in the critical location where the slip amplitude is within its critical occurs earlier.