Abstract: Wireless sensor networks (WSN) consists of many
sensor nodes that are placed on unattended environments such as
military sites in order to collect important information.
Implementing a secure protocol that can prevent forwarding forged
data and modifying content of aggregated data and has low delay
and overhead of communication, computing and storage is very
important. This paper presents a new protocol for concealed data
aggregation (CDA). In this protocol, the network is divided to
virtual cells, nodes within each cell produce a shared key to send
and receive of concealed data with each other. Considering to data
aggregation in each cell is locally and implementing a secure
authentication mechanism, data aggregation delay is very low and
producing false data in the network by malicious nodes is not
possible. To evaluate the performance of our proposed protocol, we
have presented computational models that show the performance
and low overhead in our protocol.
Abstract: Recognizing human action from videos is an active
field of research in computer vision and pattern recognition. Human
activity recognition has many potential applications such as video
surveillance, human machine interaction, sport videos retrieval and
robot navigation. Actually, local descriptors and bag of visuals words
models achieve state-of-the-art performance for human action
recognition. The main challenge in features description is how to
represent efficiently the local motion information. Most of the
previous works focus on the extension of 2D local descriptors on 3D
ones to describe local information around every interest point. In this
paper, we propose a new spatio-temporal descriptor based on a spacetime
description of moving points. Our description is focused on an
Accordion representation of video which is well-suited to recognize
human action from 2D local descriptors without the need to 3D
extensions. We use the bag of words approach to represent videos.
We quantify 2D local descriptor describing both temporal and spatial
features with a good compromise between computational complexity
and action recognition rates. We have reached impressive results on
publicly available action data set
Abstract: This paper presents a new function expansion method for finding traveling wave solution of a non-linear equation and calls it the (G'/G)-expansion method. The shallow water wave equation is reduced to a non linear ordinary differential equation by using a simple transformation. As a result the traveling wave solutions of shallow water wave equation are expressed in three forms: hyperbolic solutions, trigonometric solutions and rational solutions.
Abstract: The amount and heterogeneity of data in biomedical research, notably in interdisciplinary research, requires new methods for the collection, presentation and analysis of information. Important data from laboratory experiments as well as patient trials are available but come out of distributed resources. The Charite Medical School in Berlin has established together with the German Research Foundation (DFG) a new information service center for kidney diseases and transplantation (Open European Nephrology Science Centre - OpEN.SC). The system is based on a service-oriented architecture (SOA) with main and auxiliary modules arranged in four layers. To improve the reuse and efficient arrangement of the services the functionalities are described as business processes using the standardised Business Process Execution Language (BPEL).
Abstract: This paper presents an economic game for sybil
detection in a distributed computing environment. Cost parameters
reflecting impacts of different sybil attacks are introduced in the sybil
detection game. The optimal strategies for this game in which both
sybil and non-sybil identities are expected to participate are devised.
A cost sharing economic mechanism called Discriminatory
Rewarding Mechanism for Sybil Detection is proposed based on this
game. A detective accepts a security deposit from each active agent,
negotiates with the agents and offers rewards to the sybils if the latter
disclose their identity. The basic objective of the detective is to
determine the optimum reward amount for each sybil which will
encourage the maximum possible number of sybils to reveal
themselves. Maintaining privacy is an important issue for the
mechanism since the participants involved in the negotiation are
generally reluctant to share their private information. The mechanism
has been applied to Tor by introducing a reputation scoring function.
Abstract: Virtual touch screen using camera is an ordinary screen which uses a camera to imitate the touch screen by taking a picture of an indicator, e.g., finger, which is laid on the screen, converting the indicator tip position on the picture to the position on the screen, and moving the cursor on the screen to that position. In fact, the indicator is not laid on the screen directly, but it is intervened by the cover at some intervals. In spite of this gap, if the eye-indicator-camera angle is not large, the mapping from the indicator tip positions on the image to the corresponding cursor positions on the screen is not difficult and could be done with a little error. However, the larger the angle is, the bigger the error in the mapping occurs. This paper proposes cursor position estimation model for virtual touch screen using camera which could eliminate this kind of error. The proposed model (i) moves the on-screen pilot cursor to the screen position which locates on the screen at the position just behind the indicator tip when the indicator tip has been looked from the camera position, and then (ii) converts that pilot cursor position to the desirable cursor position (the position on the screen when it has been looked from the user-s eye through the indicator tip) by using the bilinear transformation. Simulation results show the correctness of the estimated cursor position by using the proposed model.
Abstract: The emergence of the Internet has brewed the
revolution of information storage and retrieval. As most of the
data in the web is unstructured, and contains a mix of text,
video, audio etc, there is a need to mine information to cater to
the specific needs of the users without loss of important
hidden information. Thus developing user friendly and
automated tools for providing relevant information quickly
becomes a major challenge in web mining research. Most of
the existing web mining algorithms have concentrated on
finding frequent patterns while neglecting the less frequent
ones that are likely to contain outlying data such as noise,
irrelevant and redundant data. This paper mainly focuses on
Signed approach and full word matching on the organized
domain dictionary for mining web content outliers. This
Signed approach gives the relevant web documents as well as
outlying web documents. As the dictionary is organized based
on the number of characters in a word, searching and retrieval
of documents takes less time and less space.
Abstract: This paper presents the results of thermo-mechanical
characterization of Glass/Epoxy composite specimens using Infrared
Thermography technique. The specimens used for the study were
fabricated in-house with three different lay-up sequences and tested
on a servo hydraulic machine under uni-axial loading. Infrared
Camera was used for on-line monitoring surface temperature changes
of composite specimens during tensile deformation.
Experimental results showed that thermomechanical
characteristics of each type of specimens were distinct. Temperature
was found to be decreasing linearly with increasing tensile stress in
the elastic region due to thermo-elastic effect. Yield point could be
observed by monitoring the change in temperature profile during
tensile testing and this value could be correlated with the results
obtained from stress-strain response. The extent of prior plastic
deformation in the post-yield region influenced the slopes of
temperature response during tensile loading. Partial unloading and
reloading of specimens post-yield results in change in slope in elastic
and plastic regions of composite specimens.
Abstract: Medical image registration is the key technology in image guided radiation therapy (IGRT) systems. On the basis of the previous work on our IGRT prototype with a biorthogonal x-ray imaging system, we described a method focused on the 2D/2D rigid-body registration using multiresolution pyramid based mutual information in this paper. Three key steps were involved in the method ： firstly, four 2D images were obtained including two x-ray projection images and two digital reconstructed radiographies（DRRs ） as the input for the registration ； Secondly, each pair of the corresponding x-ray image and DRR image were matched using multiresolution pyramid based mutual information under the ITK registration framework ； Thirdly, we got the final couch offset through a coordinate transformation by calculating the translations acquired from the two pairs of the images. A simulation example of a parotid gland tumor case and a clinical example of an anthropomorphic head phantom were employed in the verification tests. In addition, the influence of different CT slice thickness were tested. The simulation results showed that the positioning errors were 0.068±0.070, 0.072±0.098, 0.154±0.176mm along three axes which were lateral, longitudinal and vertical. The clinical test indicated that the positioning errors of the planned isocenter were 0.066, 0.07, 2.06mm on average with a CT slice thickness of 2.5mm. It can be concluded that our method with its verified accuracy and robustness can be effectively used in IGRT systems for patient setup.
Abstract: The stereophotogrammetry modality is gaining more widespread use in the clinical setting. Registration and visualization of this data, in conjunction with conventional 3D volumetric image modalities, provides virtual human data with textured soft tissue and internal anatomical and structural information. In this investigation computed tomography (CT) and stereophotogrammetry data is acquired from 4 anatomical phantoms and registered using the trimmed iterative closest point (TrICP) algorithm. This paper fully addresses the issue of imaging artifacts around the stereophotogrammetry surface edge using the registered CT data as a reference. Several iterative algorithms are implemented to automatically identify and remove stereophotogrammetry surface edge outliers, improving the overall visualization of the combined stereophotogrammetry and CT data. This paper shows that outliers at the surface edge of stereophotogrammetry data can be successfully removed automatically.
Abstract: This study deals with the experimental investigation
and theoretical modeling of Semi crystalline polymeric materials with
a rubbery amorphous phase (HDPE) subjected to a uniaxial cyclic
tests with various maximum strain levels, even at large deformation.
Each cycle is loaded in tension up to certain maximum strain and
then unloaded down to zero stress with N number of cycles. This
work is focuses on the measure of the volume strain due to the
phenomena of damage during this kind of tests. On the basis of
thermodynamics of relaxation processes, a constitutive model for
large strain deformation has been developed, taking into account the
damage effect, to predict the complex elasto-viscoelastic-viscoplastic
behavior of material. A direct comparison between the model
predictions and the experimental data show that the model accurately
captures the material response. The model is also capable of
predicting the influence damage causing volume variation.
Abstract: There are three possible effects of Special Theory of
Relativity (STR) on a thermodynamic system. Planck and Einstein
looked upon this process as isobaric; on the other hand Ott saw it as
an adiabatic process. However plenty of logical reasons show that the
process is isotherm. Our phenomenological consideration
demonstrates that the temperature is invariant with Lorenz
transformation. In that case process is isotherm, so volume and
pressure are Lorentz covariant. If the process is isotherm the Boyles
law is Lorentz invariant. Also equilibrium constant and Gibbs energy,
activation energy, enthalpy entropy and extent of the reaction became
Lorentz invariant.
Abstract: In this study, it is investigated the stability boundary of
Functionally Graded (FG) panel under the heats and supersonic
airflows. Material properties are assumed to be temperature
dependent, and a simple power law distribution is taken. First-order
shear deformation theory (FSDT) of plate is applied to model the
panel, and the von-Karman strain- displacement relations are
adopted to consider the geometric nonlinearity due to large
deformation. Further, the first-order piston theory is used to model the
supersonic aerodynamic load acting on a panel and Rayleigh damping
coefficient is used to present the structural damping. In order to find a
critical value of the speed, linear flutter analysis of FG panels is
performed. Numerical results are compared with the previous works,
and present results for the temperature dependent material are
discussed in detail for stability boundary of the panel with various
volume fractions, and aerodynamic pressures.
Abstract: Cross layer optimization based on utility functions has
been recently studied extensively, meanwhile, numerous types of
utility functions have been examined in the corresponding literature.
However, a major drawback is that most utility functions take a fixed
mathematical form or are based on simple combining, which can
not fully exploit available information. In this paper, we formulate a
framework of cross layer optimization based on Adaptively Weighted
Utility Functions (AWUF) for fairness balancing in OFDMA networks.
Under this framework, a two-step allocation algorithm is
provided as a sub-optimal solution, whose control parameters can be
updated in real-time to accommodate instantaneous QoS constrains.
The simulation results show that the proposed algorithm achieves
high throughput while balancing the fairness among multiple users.
Abstract: This paper describes a newly designed decentralized
nonlinear control strategy to control a robot manipulator. Based on the
concept of the nonlinear state feedback theory and decentralized
concept is developed to improve the drawbacks in previous works
concerned with complicate intelligent control and low cost effective
sensor. The control methodology is derived in the sense of Lyapunov
theorem so that the stability of the control system is guaranteed. The
decentralized algorithm does not require other joint angle and velocity
information. Individual Joint controller is implemented using a digital
processor with nearly actuator to make it possible to achieve good
dynamics and modular. Computer simulation result has been
conducted to validate the effectiveness of the proposed control scheme
under the occurrence of possible uncertainties and different reference
trajectories. The merit of the proposed control system is indicated in
comparison with a classical control system.
Abstract: Many real-world data sets consist of a very high dimensional feature space. Most clustering techniques use the distance or similarity between objects as a measure to build clusters. But in high dimensional spaces, distances between points become relatively uniform. In such cases, density based approaches may give better results. Subspace Clustering algorithms automatically identify lower dimensional subspaces of the higher dimensional feature space in which clusters exist. In this paper, we propose a new clustering algorithm, ISC – Intelligent Subspace Clustering, which tries to overcome three major limitations of the existing state-of-art techniques. ISC determines the input parameter such as є – distance at various levels of Subspace Clustering which helps in finding meaningful clusters. The uniform parameters approach is not suitable for different kind of databases. ISC implements dynamic and adaptive determination of Meaningful clustering parameters based on hierarchical filtering approach. Third and most important feature of ISC is the ability of incremental learning and dynamic inclusion and exclusions of subspaces which lead to better cluster formation.
Abstract: Land with low pH soil spread widely in Indonesia
can be used for soybean (Glycine max) cultivation, however the
production is low. The use of acid tolerant soybean and acidaluminium
tolerant nitrogen-fixing bacteria formula was an
alternative way to increase soybean productivity on acid soils.
Bradyrhizobium japonicum is one of the nitrogen fixing bacteria
which can symbiose with soybean plants through root nodule
formation. Most of the nitrogen source required by soybean plants
can be provided by this symbiosis. This research was conducted to
study the influence of acid-aluminium tolerant B. japonicum strain
BJ 11 formula using peat as carrier on growth of Tanggamus and
Anjasmoro cultivar soybean planted on acid soil fields (pH 5.0-
5.5). The results showed that the inoculant was able to increase the
growth and production of soybean which were grown on fields acid
soil at Sukadana (Lampung) and Tanah Laut (South Kalimantan),
Indonesia.
Abstract: The history of money is described in relationship to the history of computing. With the transformation and acceptance of money as information, major challenges to the security of money have involved engineering, computer science, and management. Research opportunities and challenges are described as money continues its transformation into information.
Abstract: In this paper we are to find the optimum
multiwavelet for compression of electrocardiogram (ECG)
signals. At present, it is not well known which multiwavelet is
the best choice for optimum compression of ECG. In this
work, we examine different multiwavelets on 24 sets of ECG
data with entirely different characteristics, selected from MITBIH
database. For assessing the functionality of the different
multiwavelets in compressing ECG signals, in addition to
known factors such as Compression Ratio (CR), Percent Root
Difference (PRD), Distortion (D), Root Mean Square Error
(RMSE) in compression literature, we also employed the
Cross Correlation (CC) criterion for studying the
morphological relations between the reconstructed and the
original ECG signal and Signal to reconstruction Noise Ratio
(SNR). The simulation results show that the cardbal2 by the
means of identity (Id) prefiltering method to be the best
effective transformation.
Abstract: A direct connection between ElectroEncephaloGram
(EEG) and the genetic information of individuals has been
investigated by neurophysiologists and psychiatrists since 1960-s;
and it opens a new research area in the science. This paper focuses on
the person identification based on feature extracted from the EEG
which can show a direct connection between EEG and the genetic
information of subjects. In this work the full EO EEG signal of
healthy individuals are estimated by an autoregressive (AR) model
and the AR parameters are extracted as features. Here for feature
vector constitution, two methods have been proposed; in the first
method the extracted parameters of each channel are used as a
feature vector in the classification step which employs a competitive
neural network and in the second method a combination of different
channel parameters are used as a feature vector. Correct classification
scores at the range of 80% to 100% reveal the potential of our
approach for person classification/identification and are in agreement
to the previous researches showing evidence that the EEG signal
carries genetic information. The novelty of this work is in the
combination of AR parameters and the network type (competitive
network) that we have used. A comparison between the first and the
second approach imply preference of the second one.