Abstract: The agricultural organic farming is different from
conventional farming in a way that is aimed at providing a balanced
and constructive action in agricultural systems. With the increase in
intensive agriculture, undesirable changes were being observed in
ecosystems with irreparable damage being caused to the natural
equilibrium. This is the reason for the increasing interest in organic
farming as an environment friendly agricultural production method.
In the present work three red fruits produced in organic farming were
analyzed, namely raspberry, gooseberry and blueberry. The samples
were harvested in a local farm when at plain maturation. The results
obtained allowed to conclude that the blueberry contained higher
amounts of phenolic compounds, total tannins and total anthocyanins
than raspberry and gooseberry. Furthermore, the HPLC analysis
allowed to identify monomeric anthocyanins and phenolic acids in
the three fruits studied.
Abstract: Nonlinear system identification is becoming an important tool which can be used to improve control performance. This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) model for controlling a car. The vehicle must follow a predefined path by supervised learning. Backpropagation gradient descent method was performed to train the ANFIS system. The performance of the ANFIS model was evaluated in terms of training performance and classification accuracies and the results confirmed that the proposed ANFIS model has potential in controlling the non linear system.
Abstract: Like other external sorting algorithms, the presented
algorithm is a two step algorithm including internal and external
steps. The first part of the algorithm is like the other similar
algorithms but second part of that is including a new easy
implementing method which has reduced the vast number of inputoutput
operations saliently. As decreasing processor operating time
does not have any effect on main algorithm speed, any improvement
in it should be done through decreasing the number of input-output
operations. This paper propose an easy algorithm for choose the
correct record location of the final list. This decreases the time
complexity and makes the algorithm faster.
Abstract: Composite nanostructures of metal
core/semiconductor shell (Au/CdS) configuration were prepared
using organometalic method. UV-Vis spectra for the Au/CdS colloids
show initially two well separated bands, corresponding to surface
plasmon of the Au core, and the exciton of CdS shell. The absorption
of CdS shell is enhanced, while the Au plasmon band is suppressed
as the shell thickness increases. The shell sizes were estimated from
the optical spectra using the effective mass approximation model
(EMA), and compared to the sizes of the Au core and CdS shell
measured by high resolution transmission electron microscope
(HRTEM). The changes in the absorption features are discussed in
terms of gradual increase in the coupling strength of the Au core
surface plasmon and the exciton in the CdS. leading to charge
transfer and modification of electron oscillation in Au core.
Abstract: Aeration by a plunging water jet is an energetically attractive way to effect oxygen-transfer than conventional oxygenation systems. In the present study, a new type of conical shaped plunging aeration device is fabricated to generate hollow inclined ined plunging jets (jet plunge angle of π/3 ) to investigate its oxygen transfer capacity. The results suggest that the volumetric oxygen-transfer coefficient and oxygen-transfer efficiency of the conical plunging jet aerator are competitive with other types of aeration systems. Relationships of volumetric oxygen-transfer coefficient with jet power per unit volume and jet parameters are also proposed. The suggested relationships predict the volumetric oxygentransfer coefficient within a scatter of ± 15% . Further, the application of Support Vector Machines on the experimental data revealed its utility in the prediction of volumetric oxygen-transfer coefficient and development of conical plunging jet aerators.
Abstract: Demand over web services is in growing with increases number of Web users. Web service is applied by Web application. Web application size is affected by its user-s requirements and interests. Differential in requirements and interests lead to growing of Web application size. The efficient way to save store spaces for more data and information is achieved by implementing algorithms to compress the contents of Web application documents. This paper introduces an algorithm to reduce Web application size based on reduction of the contents of HTML files. It removes unimportant contents regardless of the HTML file size. The removing is not ignored any character that is predicted in the HTML building process.
Abstract: Ambient hydrolysis products in moist air and
hydrolysis kinetics in argon with humidity of RH1.5% for
polycrystalline LiH powders and sintered bulks were investigated by
X-ray diffraction, Raman spectroscopy and gravimetry. The results
showed that the hydrolysis products made up a layered structure of
LiOH•H2O/LiOH/Li2O from surface of the sample to inside. In low
humid argon atmosphere, the primary hydrolysis product was Li2O
rather than LiOH. The hydrolysis kinetic curves of LiH bulks present a
paralinear shape, which could be explained by the “Layer Diffusion
Control" model. While a three-stage hydrolysis kinetic profile was
observed for LiH powders under the same experimental conditions.
The first two sections were similar to that of the bulk samples, and the
third section also presents a linear reaction kinetics but with a smaller
reaction rate compared to the second section because of a larger
exothermic effect for the hydrolysis reaction of LiH powder.
Abstract: Wireless capsule endoscopy provides real-time images in the digestive tract. Capsule images are usually low resolution and are diverse images due to travel through various regions of human body. Color information has been a primary reference in predicting abnormalities such as bleeding. Often color is not sufficient for this purpose. In this study, we took morphological shapes into account as additional, but important criterion. First, we processed gastric images in order to indentify various objects in the image. Then, we analyzed color information in the object. In this way, we could remove unnecessary information and increase the accuracy. Compared to our previous investigations, we could handle images of various degrees of brightness and improve our diagnostic algorithm.
Abstract: MicroRNAs are an important class of gene expression
regulators that are involved in many biological processes including
embryogenesis. miR-125b is a conserved microRNA that is enriched
in the nervous system. We have previously reported the function of
miR-125b in neuronal differentiation of human cell lines. We also
discovered the function of miR-125b in regulating p53 in human and
zebrafish. Here we further characterize the brain defects in zebrafish
embryos injected with morpholinos against miR-125b. Our data
confirm the essential role of miR-125b in brain morphogenesis
particularly in maintaining the balance between proliferation, cell
death and differentiation. We identified lunatic fringe (lfng) as an
additional target of miR-125b in human and zebrafish and suggest
that lfng may mediate the function of miR-125b in neurogenesis.
Together, this report reveals new insights into the function of miR-
125b during neural development of zebrafish.
Abstract: Visual secret sharing (VSS) was proposed by Naor and Shamir in 1995. Visual secret sharing schemes encode a secret image into two or more share images, and single share image can’t obtain any information about the secret image. When superimposes the shares, it can restore the secret by human vision. Due to the traditional VSS have some problems like pixel expansion and the cost of sophisticated. And this method only can encode one secret image. The schemes of encrypting more secret images by random grids into two shares were proposed by Chen et al. in 2008. But when those restored secret images have much distortion, those schemes are almost limited in decoding. In the other words, if there is too much distortion, we can’t encrypt too much information. So, if we can adjust distortion to very small, we can encrypt more secret images. In this paper, four new algorithms which based on Chang et al.’s scheme be held in 2010 are proposed. First algorithm can adjust distortion to very small. Second algorithm distributes the distortion into two restored secret images. Third algorithm achieves no distortion for special secret images. Fourth algorithm encrypts three secret images, which not only retain the advantage of VSS but also improve on the problems of decoding.
Abstract: Text categorization - the assignment of natural language documents to one or more predefined categories based on their semantic content - is an important component in many information organization and management tasks. Performance of neural networks learning is known to be sensitive to the initial weights and architecture. This paper discusses the use multilayer neural network initialization with decision tree classifier for improving text categorization accuracy. An adaptation of the algorithm is proposed in which a decision tree from root node until a final leave is used for initialization of multilayer neural network. The experimental evaluation demonstrates this approach provides better classification accuracy with Reuters-21578 corpus, one of the standard benchmarks for text categorization tasks. We present results comparing the accuracy of this approach with multilayer neural network initialized with traditional random method and decision tree classifiers.
Abstract: The paper deals with the analysis of the dynamic
response of footbridges under human - induced dynamic loads.
This is a frequently occurring and often dominant load for
footbridges as it stems from the very purpose of a footbridge - to
convey pedestrian. Due to the emergence of new materials and
advanced engineering technology, slender footbridges are
increasingly becoming popular to satisfy the modern transportation
needs and the aesthetical requirements of the society. These
structures however are always lively with low stiffness, low mass,
low damping and low natural frequencies. As a consequence, they are
prone to vibration induced by human activities and can suffer severe
vibration serviceability problems, particularly in the lateral direction.
Pedestrian bridges are designed according to first and second limit
states, these are the criteria involved in response to static design load.
However, it is necessary to assess the dynamic response of bridge
design load on pedestrians and assess it impact on the comfort of the
user movement. Usually the load is considered a person or a small
group which can be assumed in perfect motion synchronization.
Already one person or small group can excite significant vibration of
the deck. In order to calculate the dynamic response to the movement
of people, designer needs available and suitable computational model
and criteria. For the calculation program ANSYS based on finite
element method was used.
Abstract: The wireless mesh networks (WMNs) are emerging technology in wireless networking as they can serve large scale high speed internet access. Due to its wireless multi-hop feature, wireless mesh network is prone to suffer from many attacks, such as denial of service attack (DoS). We consider a special case of DoS attack which is selective forwarding attack (a.k.a. gray hole attack). In such attack, a misbehaving mesh router selectively drops the packets it receives rom its predecessor mesh router. It is very hard to detect that packet loss is due to medium access collision, bad channel quality or because of selective forwarding attack. In this paper, we present a review of detection algorithms of selective forwarding attack and discuss their advantage & disadvantage. Finally we conclude this paper with open research issues and challenges.
Abstract: The optimal design of PI controller for Automatic Generation Control in two area is presented in this paper. The concept of Dual mode control is applied in the PI controller, such that the proportional mode is made active when the rate of change of the error is sufficiently larger than a specified limit otherwise switched to the integral mode. A digital simulation is used in conjunction with the Hooke-Jeeve’s optimization technique to determine the optimum parameters (individual gain of proportional and integral controller) of the PI controller. Integrated Square of the Error (ISE), Integrated Time multiplied by Absolute Error(ITAE) , and Integrated Absolute Error(IAE) performance indices are considered to measure the appropriateness of the designed controller. The proposed controller are tested for a two area single nonreheat thermal system considering the practical aspect of the problem such as Deadband and Generation Rate Constraint(GRC). Simulation results show that dual mode with optimized values of the gains improved the control performance than the commonly used Variable Structure .
Abstract: Multiple-Input-Multiple-Output (MIMO) is one of the most important communication techniques that allow wireless systems to achieve higher data rate. To overcome the practical difficulties in implementing Dirty Paper Coding (DPC), various suboptimal MIMO Broadcast (MIMO-BC) scheduling algorithms are employed which choose the best set of users among all the users. In this paper we discuss such a sub-optimal MIMO-BC scheduling algorithm which employs antenna selection at the receiver side. The channels for the users considered here are not Identical and Independent Distributed (IID) so that users at the receiver side do not get equal opportunity for communication. So we introduce a method of applying weights to channels of the users which are not IID in such a way that each of the users gets equal opportunity for communication. The effect of weights on overall sum-rate achieved by the system has been investigated and presented.
Abstract: The authors present an optimization algorithm for order reduction and its application for the determination of the relative mapping errors of linear time invariant dynamic systems by the simplified models. These relative mapping errors are expressed by means of the relative integral square error criterion, which are determined for both unit step and impulse inputs. The reduction algorithm is based on minimization of the integral square error by particle swarm optimization technique pertaining to a unit step input. The algorithm is simple and computer oriented. It is shown that the algorithm has several advantages, e.g. the reduced order models retain the steady-state value and stability of the original system. Two numerical examples are solved to illustrate the superiority of the algorithm over some existing methods.
Abstract: This paper is on the general discussion of memory consistency model like Strict Consistency, Sequential Consistency, Processor Consistency, Weak Consistency etc. Then the techniques for implementing distributed shared memory Systems and Synchronization Primitives in Software Distributed Shared Memory Systems are discussed. The analysis involves the performance measurement of the protocol concerned that is Multiple Writer Protocol. Each protocol has pros and cons. So, the problems that are associated with each protocol is discussed and other related things are explored.
Abstract: Recent scientific investigations indicate that
multimodal biometrics overcome the technical limitations of
unimodal biometrics, making them ideally suited for everyday life
applications that require a reliable authentication system. However,
for a successful adoption of multimodal biometrics, such systems
would require large heterogeneous datasets with complex multimodal
fusion and privacy schemes spanning various distributed
environments. From experimental investigations of current
multimodal systems, this paper reports the various issues related to
speed, error-recovery and privacy that impede the diffusion of such
systems in real-life. This calls for a robust mechanism that caters to
the desired real-time performance, robust fusion schemes,
interoperability and adaptable privacy policies.
The main objective of this paper is to present a framework that
addresses the abovementioned issues by leveraging on the
heterogeneous resource sharing capacities of Grid services and the
efficient machine learning capabilities of artificial neural networks
(ANN). Hence, this paper proposes a Grid-based neural network
framework for adopting multimodal biometrics with the view of
overcoming the barriers of performance, privacy and risk issues that
are associated with shared heterogeneous multimodal data centres.
The framework combines the concept of Grid services for reliable
brokering and privacy policy management of shared biometric
resources along with a momentum back propagation ANN (MBPANN)
model of machine learning for efficient multimodal fusion and
authentication schemes. Real-life applications would be able to adopt
the proposed framework to cater to the varying business requirements
and user privacies for a successful diffusion of multimodal
biometrics in various day-to-day transactions.
Abstract: Face authentication for access control is a face
membership authentication which passes the person of the incoming
face if he turns out to be one of an enrolled person based on face
recognition or rejects if not. Face membership authentication belongs
to the two class classification problem where SVM(Support Vector
Machine) has been successfully applied and shows better performance
compared to the conventional threshold-based classification. However,
most of previous SVMs have been trained using image feature vectors
extracted from face images of each class member(enrolled
class/unenrolled class) so that they are not robust to variations in
illuminations, poses, and facial expressions and much affected by
changes in member configuration of the enrolled class
In this paper, we propose an effective face membership
authentication method based on SVM using class discriminating
features which represent an incoming face image-s associability with
each class distinctively. These class discriminating features are weakly
related with image features so that they are less affected by variations
in illuminations, poses and facial expression.
Through experiments, it is shown that the proposed face
membership authentication method performs better than the threshold
rule-based or the conventional SVM-based authentication methods and
is relatively less affected by changes in member size and membership.
Abstract: As the Social network game(SNG) is rising
dramatically worldwide, an interesting aspect has appeared in the
demographic analysis. That is the ratio of the game users by gender.
Although the ratio of male and female users in online game was
60:40% previously, the ratio of male and female users in SNG stood at
47:53% which shows that the ratio of female users is higher than that
of male users. Here, it should be noted that 35% in those 53% female
users are the first-time users of game. This fact suggests that women
who were not interested in game previously has taken an interest in
SNG. Notwithstanding this issue, there have been little studies on the
female users of SNG although there are many studies that analyzed the
tendency of female users- online game play. This study conducted the
analyzed how the game-playing tendency of SNG gamers was
manifested in the game by gender. For that, this study will identify the
tendency of SNG users by gender based on the preceding studies that
analyzed the online game users by gender. The subject of this study
was confined to the farm and urban construction simulation games
which were offered based on the mobile application platform.
Regarding the methodology of study, the first focus group
interview(FGI) was conducted with the male and female users who
had played games on Social network service(SNS) until recently. Later,
the second one-on-one in-depth interview was conducted to gain an
insight into the psychological state of the subjects.