Abstract: As mobile ad hoc networks (MANET) have different
characteristics from wired networks and even from standard wireless
networks, there are new challenges related to security issues that
need to be addressed. Due to its unique features such as open nature,
lack of infrastructure and central management, node mobility and
change of dynamic topology, prevention methods from attacks on
them are not enough. Therefore intrusion detection is one of the
possible ways in recognizing a possible attack before the system
could be penetrated. All in all, techniques for intrusion detection in
old wireless networks are not suitable for MANET. In this paper, we
classify the architecture for Intrusion detection systems that have so
far been introduced for MANETs, and then existing intrusion
detection techniques in MANET presented and compared. We then
indicate important future research directions.
Abstract: fifteen cultivars of Strawberries (Queen Eliza, Sequia,
Paros, Mcdonance, Selva, Chandler, Mrak, Ten beauty, Aliso, Pajero,
Kordestan, Camarosa, Blackmore, Gaviota and Fresno) were
investigated in 2011, under hydroponic system condition. Yield and
fruit Firmness was determinate. Chemical analyses of soluble solids
content (SSC), titratable acidity (TA), ascorbic acid (AA) and pH
were done. 4 cultivars (Aliso, Selva, Paros and Gaviota) yielded more
than 250 g/plant, while cultivar Black more, Fresno and Kordestan
produced less than 100g/plant. The amounts of fruit firmness
indicated that 'Camarosa' fruit was firmer than others cultivars.
Cultivar 'Fresno' had the highest pH (3.27). Ttitratable acidity varied
from 1.03g/l00g for cultivar 'Sequia' and 'Gaviota' to 1.48g/l00g for
cultivar 'Chandler'. Fresno, Kordestan, Aliso and Chandler showed
the highest soluble solid concentration. Ascorbic acid averaged for
most cultivars between 30.26 and 79.73 mg/100gf.w. Present results
showed that different cultivars of strawberry contain highly variable
in fruit quality.
Abstract: The wireless sensor networks have been extensively
deployed and researched. One of the major issues in wireless sensor
networks is a developing energy-efficient clustering protocol.
Clustering algorithm provides an effective way to prolong the lifetime
of a wireless sensor networks. In the paper, we compare several
clustering protocols which significantly affect a balancing of energy
consumption. And we propose an Energy-Efficient Distributed
Unequal Clustering (EEDUC) algorithm which provides a new way of
creating distributed clusters. In EEDUC, each sensor node sets the
waiting time. This waiting time is considered as a function of residual
energy, number of neighborhood nodes. EEDUC uses waiting time to
distribute cluster heads. We also propose an unequal clustering
mechanism to solve the hot-spot problem. Simulation results show that
EEDUC distributes the cluster heads, balances the energy
consumption well among the cluster heads and increases the network
lifetime.
Abstract: This paper proposes a methodology for analysis of
the dynamic behavior of a robotic manipulator in continuous
time. Initially this system (nonlinear system) will be decomposed
into linear submodels and analyzed in the context of the Linear
and Parameter Varying (LPV) Systems. The obtained linear
submodels, which represent the local dynamic behavior of the
robotic manipulator in some operating points were grouped in
a Takagi-Sugeno fuzzy structure. The obtained fuzzy model was
analyzed and validated through analog simulation, as universal
approximator of the robotic manipulator.
Abstract: In this paper we consider a one-dimensional random
geometric graph process with the inter-nodal gaps evolving according
to an exponential AR(1) process. The transition probability matrix
and stationary distribution are derived for the Markov chains concerning
connectivity and the number of components. We analyze the
algorithm for hitting time regarding disconnectivity. In addition to
dynamical properties, we also study topological properties for static
snapshots. We obtain the degree distributions as well as asymptotic
precise bounds and strong law of large numbers for connectivity
threshold distance and the largest nearest neighbor distance amongst
others. Both exact results and limit theorems are provided in this
paper.
Abstract: The shortest path routing problem is a multiobjective
nonlinear optimization problem with constraints. This problem has
been addressed by considering Quality of service parameters, delay
and cost objectives separately or as a weighted sum of both
objectives. Multiobjective evolutionary algorithms can find multiple
pareto-optimal solutions in one single run and this ability makes them
attractive for solving problems with multiple and conflicting
objectives. This paper uses an elitist multiobjective evolutionary
algorithm based on the Non-dominated Sorting Genetic Algorithm
(NSGA), for solving the dynamic shortest path routing problem in
computer networks. A priority-based encoding scheme is proposed
for population initialization. Elitism ensures that the best solution
does not deteriorate in the next generations. Results for a sample test
network have been presented to demonstrate the capabilities of the
proposed approach to generate well-distributed pareto-optimal
solutions of dynamic routing problem in one single run. The results
obtained by NSGA are compared with single objective weighting
factor method for which Genetic Algorithm (GA) was applied.
Abstract: The growth of the aquaculture industry has been
associated with negative environmental impacts through the
discharge of raw effluents into the adjacent receiving water bodies.
Macrophytes from natural saline lakes, which have adaptability to the
high salinity, can be suitable for saline effluent treatment. Eight
emergent species from natural saline area were planted in an
experimental gravel bed hydroponic mesocosm (GBH) which was
treated with effluent water from an intensive fish farm using
geothermal water. In order to examine the applicability of the
halophytes in treatment processes, we tested the relative efficacy of
total nitrogen (TN), total phosphorus (TP), potassium (K), sodium
(Na), magnesium (Mg) and calcium (Ca) removal for the saline
wastewater treatment. Four of the eight species, which were
Phragmites australis, Typha angustifolia, Glyceria maxima, Scirpus
lacustris spp. tabernaemontani could survive and contribute the
experimental treatment.
Abstract: This paper proposes a Particle Swarm Optimization
(PSO) based technique for the optimal allocation of Distributed
Generation (DG) units in the power systems. In this paper our aim is
to decide optimal number, type, size and location of DG units for
voltage profile improvement and power loss reduction in distribution
network. Two types of DGs are considered and the distribution load
flow is used to calculate exact loss. Load flow algorithm is combined
appropriately with PSO till access to acceptable results of this
operation. The suggested method is programmed under MATLAB
software. Test results indicate that PSO method can obtain better
results than the simple heuristic search method on the 30-bus and 33-
bus radial distribution systems. It can obtain maximum loss reduction
for each of two types of optimally placed multi-DGs. Moreover,
voltage profile improvement is achieved.
Abstract: This paper presents a conceptual model of agreement
options for negotiation support in multi-person decision on
optimizing high-rise building columns. The decision is complicated
since many parties involved in choosing a single alternative from a
set of solutions. There are different concern caused by differing
preferences, experiences, and background. Such building columns as
alternatives are referred to as agreement options which are
determined by identifying the possible decision maker group,
followed by determining the optimal solution for each group. The
group in this paper is based on three-decision makers preferences that
are designer, programmer, and construction manager. Decision
techniques applied to determine the relative value of the alternative
solutions for performing the function. Analytical Hierarchy Process
(AHP) was applied for decision process and game theory based agent
system for coalition formation. An n-person cooperative game is
represented by the set of all players. The proposed coalition
formation model enables each agent to select individually its allies or
coalition. It further emphasizes the importance of performance
evaluation in the design process and value-based decision.
Abstract: Artificial Immune System is adopted as a Heuristic
Algorithm to solve the combinatorial problems for decades.
Nevertheless, many of these applications took advantage of the benefit
for applications but seldom proposed approaches for enhancing the
efficiency. In this paper, we continue the previous research to develop
a Self-evolving Artificial Immune System II via coordinating the T
and B cell in Immune System and built a block-based artificial
chromosome for speeding up the computation time and better
performance for different complexities of problems. Through the
design of Plasma cell and clonal selection which are relative the
function of the Immune Response. The Immune Response will help
the AIS have the global and local searching ability and preventing
trapped in local optima. From the experimental result, the significant
performance validates the SEAIS II is effective when solving the
permutation flows-hop problems.
Abstract: In this paper, we introduce an e-collaborative learning circles methodology which utilizes the information and communication technologies (ICTs) in e-educational processes. In e-collaborative learning circles methodology, the teachers and students announce their research projects on various mailing lists and discussion boards using available ICTs. The teachers & moderators and students who are already members of the e-forums, discuss the project proposals in their classrooms sent out by the potential global partner schools and return the requested feed back to the proposing school(s) about their level of the participation and contribution in the research. In general, an e-collaborative learning circle project is implemented with a small and diverse group (usually 8-10 participants) from around the world. The students meet regularly over a period of weeks/months through the ICTs during the ecollaborative learning process. When the project is completed, a project product (e-book / DVD) is prepared and sent to the circle members. In this research, when taking into account the interests and motivation of the participating students with the facilitating role of the teacher(s), the students in each circle do research to obtain new data and information, thus enabling them to have the opportunity to meet both different cultures and international understandings across the globe. However, while the participants communicate along with the members in the circle they also practice and develop their communication language skills. Finally, teachers and students find the possibility to develop their skills in using the ICTs as well.
Abstract: This paper seeks to explore the actual classroom
setting, to examine its role for students- learning, and attitude in the
class. It presents a theoretical approach of the classroom as system to
be explored and examines the concrete reality of Greek secondary
education students, under the light of the above approach. Based on
the findings of a quantitative and qualitative research, authors
propose a rather ontological approach of the classroom and underline
what the key-elements for such approach should be. The paper
explores extensively the theoretical dimensions for the change of
paradigm required and addresses the new issues to be considered.
Abstract: In Image processing the Image compression can improve
the performance of the digital systems by reducing the cost and
time in image storage and transmission without significant reduction
of the Image quality. This paper describes hardware architecture of
low complexity Discrete Cosine Transform (DCT) architecture for
image compression[6]. In this DCT architecture, common computations
are identified and shared to remove redundant computations
in DCT matrix operation. Vector processing is a method used for
implementation of DCT. This reduction in computational complexity
of 2D DCT reduces power consumption. The 2D DCT is performed
on 8x8 matrix using two 1-Dimensional Discrete cosine transform
blocks and a transposition memory [7]. Inverse discrete cosine
transform (IDCT) is performed to obtain the image matrix and
reconstruct the original image. The proposed image compression
algorithm is comprehended using MATLAB code. The VLSI design
of the architecture is implemented Using Verilog HDL. The proposed
hardware architecture for image compression employing DCT was
synthesized using RTL complier and it was mapped using 180nm
standard cells. . The Simulation is done using Modelsim. The
simulation results from MATLAB and Verilog HDL are compared.
Detailed analysis for power and area was done using RTL compiler
from CADENCE. Power consumption of DCT core is reduced to
1.027mW with minimum area[1].
Abstract: Since communications between tag and reader in RFID
system are by radio, anyone can access the tag and obtain its any
information. And a tag always replies with the same ID so that it is
hard to distinguish between a real and a fake tag. Thus, there are many
security problems in today-s RFID System. Firstly, unauthorized
reader can easily read the ID information of any Tag. Secondly,
Adversary can easily cheat the legitimate reader using the collected
Tag ID information, such as the any legitimate Tag. These security
problems can be typically solved by encryption of messages
transmitted between Tag and Reader and by authentication for Tag.
In this paper, to solve these security problems on RFID system, we
propose the Tag Authentication Scheme based on self shrinking
generator (SSG). SSG Algorithm using in our scheme is proposed by
W.Meier and O.Staffelbach in EUROCRYPT-94. This Algorithm is
organized that only one LFSR and selection logic in order to generate
random stream. Thus it is optimized to implement the hardware logic
on devices with extremely limited resource, and the output generating
from SSG at each time do role as random stream so that it is allow our
to design the light-weight authentication scheme with security against
some network attacks. Therefore, we propose the novel tag
authentication scheme which use SSG to encrypt the Tag-ID
transmitted from tag to reader and achieve authentication of tag.
Abstract: The proposed multiplexer-based novel 1-bit full
adder cell is schematized by using DSCH2 and its layout is generated
by using microwind VLSI CAD tool. The adder cell layout
interconnect analysis is performed by using BSIM4 layout analyzer.
The adder circuit is compared with other six existing adder circuits
for parametric analysis. The proposed adder cell gives better
performance than the other existing six adder circuits in terms of
power, propagation delay and PDP. The proposed adder circuit is
further analyzed for interconnect analysis, which gives better
performance than other adder circuits in terms of layout thickness,
width and height.
Abstract: In this paper, an efficient local appearance feature
extraction method based the multi-resolution Curvelet transform is
proposed in order to further enhance the performance of the well
known Linear Discriminant Analysis(LDA) method when applied
to face recognition. Each face is described by a subset of band
filtered images containing block-based Curvelet coefficients. These
coefficients characterize the face texture and a set of simple statistical
measures allows us to form compact and meaningful feature vectors.
The proposed method is compared with some related feature extraction
methods such as Principal component analysis (PCA), as well
as Linear Discriminant Analysis LDA, and independent component
Analysis (ICA). Two different muti-resolution transforms, Wavelet
(DWT) and Contourlet, were also compared against the Block Based
Curvelet-LDA algorithm. Experimental results on ORL, YALE and
FERET face databases convince us that the proposed method provides
a better representation of the class information and obtains much
higher recognition accuracies.
Abstract: The pipe inspection operation is the difficult detective
performance. Almost applications are mainly relies on a manual
recognition of defective areas that have carried out detection by an
engineer. Therefore, an automation process task becomes a necessary
in order to avoid the cost incurred in such a manual process. An
automated monitoring method to obtain a complete picture of the
sewer condition is proposed in this work. The focus of the research is
the automated identification and classification of discontinuities in
the internal surface of the pipe. The methodology consists of several
processing stages including image segmentation into the potential
defect regions and geometrical characteristic features. Automatic
recognition and classification of pipe defects are carried out by means
of using an artificial neural network technique (ANN) based on
Radial Basic Function (RBF). Experiments in a realistic environment
have been conducted and results are presented.
Abstract: In this paper, we present an approach for soccer video
edition using a multimodal annotation. We propose to associate with
each video sequence of a soccer match a textual document to be used
for further exploitation like search, browsing and abstract edition.
The textual document contains video meta data, match meta data, and
match data. This document, generated automatically while the video
is analyzed, segmented and classified, can be enriched semi
automatically according to the user type and/or a specialized
recommendation system.
Abstract: A new approach based on the consideration that electroencephalogram (EEG) signals are chaotic signals was presented for automated diagnosis of electroencephalographic changes. This consideration was tested successfully using the nonlinear dynamics tools, like the computation of Lyapunov exponents. This paper presented the usage of statistics over the set of the Lyapunov exponents in order to reduce the dimensionality of the extracted feature vectors. Since classification is more accurate when the pattern is simplified through representation by important features, feature extraction and selection play an important role in classifying systems such as neural networks. Multilayer perceptron neural network (MLPNN) architectures were formulated and used as basis for detection of electroencephalographic changes. Three types of EEG signals (EEG signals recorded from healthy volunteers with eyes open, epilepsy patients in the epileptogenic zone during a seizure-free interval, and epilepsy patients during epileptic seizures) were classified. The selected Lyapunov exponents of the EEG signals were used as inputs of the MLPNN trained with Levenberg- Marquardt algorithm. The classification results confirmed that the proposed MLPNN has potential in detecting the electroencephalographic changes.
Abstract: Wireless Sensor networks have a wide spectrum of civil and military applications that call for secure communication such as the terrorist tracking, target surveillance in hostile environments. For the secure communication in these application areas, we propose a method for generating a hierarchical key structure for the efficient group key management. In this paper, we apply A* algorithm in generating a hierarchical key structure by considering the history data of the ratio of addition and eviction of sensor nodes in a location where sensor nodes are deployed. Thus generated key tree structure provides an efficient way of managing the group key in terms of energy consumption when addition and eviction event occurs. A* algorithm tries to minimize the number of messages needed for group key management by the history data. The experimentation with the tree shows efficiency of the proposed method.