Abstract: Wireless Sensor Networks consist of inexpensive, low power sensor nodes deployed to monitor the environment and collect
data. Gathering information in an energy efficient manner is a critical aspect to prolong the network lifetime. Clustering algorithms have an advantage of enhancing the network lifetime. Current clustering algorithms usually focus on global re-clustering and local re-clustering separately. This paper, proposed a combination of those two reclustering methods to reduce the energy consumption of the network. Furthermore, the proposed algorithm can apply to homogeneous as well as heterogeneous wireless sensor networks. In addition, the cluster head rotation happens, only when its energy drops below a dynamic threshold value computed by the algorithm. The simulation result shows that the proposed algorithm prolong the network lifetime compared to existing algorithms.
Abstract: Among all microRNAs (miRNAs) in 12 plant species investigated in this study, only miR398 targeted the copper chaperone for superoxide dismutase (CCS). The nucleotide sequences of miRNA binding sites were located in the mRNA protein-coding sequence (CDS) and were highly homologous. These binding sites in CCS mRNA encoded a conservative GDLGTL hexapeptide. The binding sites for miR398 in the CDS of superoxide dismutase 1 mRNA encoded GDLGN pentapeptide. The conservative miR398 binding site located in the CDS of superoxide dismutase 2 mRNA encoded the GDLGNI hexapeptide. The miR398 binding site in the CDS of superoxide dismutase 3 mRNA encoded the GDLGNI or GDLGNV hexapeptide. Gene expression of the entire superoxide dismutase family in the studied plant species was regulated only by miR398. All members of the miR398 family, i.e. miR398a,b,c were connected to one site for each CuZnSOD and chaperone mRNA.
Abstract: Autism Spectrum Disorders (ASDs) are characterized
by abnormalities in social interaction and communication, as well as
repetitive and stereotyped behaviors. Although various studies have
been conducted in ASDs etiology across the world, it seems that they
are still unknown in Middle East. Some scientific researches have
been conducted on ASDs in Middle East (ME) especially in
Kingdom of Saudi Arabia (KSA).
A systematic literature review was performed to identify the ASDs
studies in KSA. Accordingly, PubMed, ISI web of Science and
Google were searched to find KSA and ME studies in ASDs. The
main focus of this review work is to outline an improved
understanding of the underpinnings of ASD in order to achieve
therapeutic interventions and we will discuss the main problem we
waiting for solution with reference with role of Transcranial
Magnetic Stimulation (TMS) to modulate cortical activity improve
understanding ASD.
Abstract: Increased energy demand and the concern about
environment friendly technology, renewable bio-fuels are better
alternative to petroleum products. In the present study linseed oil was
used as alternative source for diesel engine fuel and the results were
compared with baseline data of neat diesel. Performance parameters
such as brake thermal efficiency (BTE) and brake specific fuel
consumption (BSFC) and emissions parameters such as CO,
unburned hydro carbon (UBHC), NOx, CO2 and exhaust temperature
were compared. BTE of the engine was lower and BSFC was higher
when the engine was fueled with Linseed oil compared to diesel fuel.
Emission characteristics are better than diesel fuel. NOx formation by
using linseed oil during the experiment was lower than diesel fuel.
Linseed oil is non edible oil, so it can be used as an extender of diesel
fuel energy source for small and medium energy needs.
Abstract: The purpose of this paper is to present the design and
instrumentation of a new benchmark multivariable nonlinear control
laboratory. The mathematical model of this system may be used to
test the applicability and performance of various nonlinear control
procedures. The system is a two degree-of-freedom robotic arm with
soft and hard (discontinuous) nonlinear terms. Two novel
mechanisms are designed to allow the implementation of adjustable
Coulomb friction and backlash.
Abstract: A statistical optimization was studied to design a media composition to produce optimum cellulolytic enzyme where palm oil mill effluent (POME) as a basal medium and filamentous fungus, Trichoderma reesei RUT-C30 were used in the liquid state bioconversion(LSB). 2% (w/v) total suspended solid, TSS, of the POME supplemented with 1% (w/v) cellulose, 0.5%(w/v) peptone and 0.02% (v/v) Tween 80 was estimated to produce the optimum CMCase activity of 18.53 U/ml through the statistical analysis followed by the faced centered central composite design(FCCCD). The probability values of cellulose (
Abstract: The power system network is becoming more
complex nowadays and it is very difficult to maintain the stability
of the system. Today-s enhancement of technology makes it
possible to include new energy storage devices in the electric
power system. In addition, with the aid of power electronic
devices, it is possible to independently exchange active and
reactive power flow with the utility grid. The main purpose of this
paper proposes a Proportional – Integral (PI) control based 48 –
pulse Inverter based Static Synchronous Series Compensator
(SSSC) with and without Superconducting Magnetic Energy
Storage (SMES) used for enhancing the transient stability and
regulating power flow in automatic mode. Using a test power
system through the dynamic simulation in Matlab/Simulink
platform validates the performance of the proposed SSSC with and
without SMES system.
Abstract: The periodic mixed convection of a water-copper
nanofluid inside a rectangular cavity with aspect ratio of 3 is
investigated numerically. The temperature of the bottom wall of the
cavity is assumed greater than the temperature of the top lid which
oscillates horizontally with the velocity defined as u = u0 sin (ω t).
The effects of Richardson number, Ri, and volume fraction of
nanoparticles on the flow and thermal behavior of the nanofluid are
investigated. Velocity and temperature profiles, streamlines and
isotherms are presented. It is observed that when Ri < 1, heat transfer
rate is much greater than when Ri > 1. The higher value of Ri
corresponds to a lower value of the amplitude of the oscillation of
Num in the steady periodic state. Moreover, increasing the volume
fraction of the nanoparticles increases the heat transfer rate.
Abstract: The present paper is a case study about exploitation of
Kheir Abad river (Khoozestan, Iran) water resources and the
problems caused by river sediments around the pumping stations.
The weak points and strong points of Boneh Basht pumping station
have been studied by experienced experts, work teams, and
consulting engineers and technical and executive solutions have been
suggested. Therefore, the suggestions of this article are based on the
performed studies and are proposed in order to evaluate the logical
solutions.
Rather complicated processes resulting from the interaction of
water flows and sediments observed at Boneh Basht pumping station
occur at other pumping stations in almost the same way. Therefore,
Boneh Basht pumping station can be selected as a sample (pilot) and
up-to-date theories and experiences can be applied to this station and
the results can be offered to other stations.
Abstract: A high-linearity and high-speed current-mode sampleand-
hold circuit is designed and simulated using a 0.25μm CMOS
technology. This circuit design is based on low voltage and it utilizes
a fully differential circuit. Due to the use of only two switches the
switch related noise has been reduced. Signal - dependent -error is
completely eliminated by a new zero voltage switching technique.
The circuit has a linearity error equal to ±0.05μa, i.e. 12-bit
accuracy with a ±160 μa differential output - input signal frequency
of 5MHZ, and sampling frequency of 100 MHZ. Third
harmonic is equal to –78dB.
Abstract: The most important property of the Gene Ontology is
the terms. These control vocabularies are defined to provide
consistent descriptions of gene products that are shareable and
computationally accessible by humans, software agent, or other
machine-readable meta-data. Each term is associated with
information such as definition, synonyms, database references, amino
acid sequences, and relationships to other terms. This information has
made the Gene Ontology broadly applied in microarray and
proteomic analysis. However, the process of searching the terms is
still carried out using traditional approach which is based on keyword
matching. The weaknesses of this approach are: ignoring semantic
relationships between terms, and highly depending on a specialist to
find similar terms. Therefore, this study combines semantic similarity
measure and genetic algorithm to perform a better retrieval process
for searching semantically similar terms. The semantic similarity
measure is used to compute similitude strength between two terms.
Then, the genetic algorithm is employed to perform batch retrievals
and to handle the situation of the large search space of the Gene
Ontology graph. The computational results are presented to show the
effectiveness of the proposed algorithm.
Abstract: The multiindex Mittag-Leffler (M-L) function and the multiindex Dzrbashjan-Gelfond-Leontiev (D-G-L) differentiation and integration play a very pivotal role in the theory and applications of generalized fractional calculus. The object of this paper is to investigate the relations that exist between the Riemann-Liouville fractional calculus and multiindex Dzrbashjan-Gelfond-Leontiev differentiation and integration with multiindex Mittag-Leffler function.
Abstract: In this paper we present a substantiation of a new
Laguerre-s type iterative method for solving of a nonlinear
polynomial equations systems with real coefficients. The problems of
its implementation, including relating to the structural choice of
initial approximations, were considered. Test examples demonstrate
the effectiveness of the method at the solving of many practical
problems solving.
Abstract: this paper presents an auto-regressive network called the Auto-Regressive Multi-Context Recurrent Neural Network (ARMCRN), which forecasts the daily peak load for two large power plant systems. The auto-regressive network is a combination of both recurrent and non-recurrent networks. Weather component variables are the key elements in forecasting because any change in these variables affects the demand of energy load. So the AR-MCRN is used to learn the relationship between past, previous, and future exogenous and endogenous variables. Experimental results show that using the change in weather components and the change that occurred in past load as inputs to the AR-MCRN, rather than the basic weather parameters and past load itself as inputs to the same network, produce higher accuracy of predicted load. Experimental results also show that using exogenous and endogenous variables as inputs is better than using only the exogenous variables as inputs to the network.
Abstract: The paper explores the development of an optimization of method and apparatus for retrieving extended high dynamic range from digital negative image. Architectural photo imaging can benefit from high dynamic range imaging (HDRI) technique for preserving and presenting sufficient luminance in the shadow and highlight clipping image areas. The HDRI technique that requires multiple exposure images as the source of HDRI rendering may not be effective in terms of time efficiency during the acquisition process and post-processing stage, considering it has numerous potential imaging variables and technical limitations during the multiple exposure process. This paper explores an experimental method and apparatus that aims to expand the dynamic range from digital negative image in HDRI environment. The method and apparatus explored is based on a single source of RAW image acquisition for the use of HDRI post-processing. It will cater the optimization in order to avoid and minimize the conventional HDRI photographic errors caused by different physical conditions during the photographing process and the misalignment of multiple exposed image sequences. The study observes the characteristics and capabilities of RAW image format as digital negative used for the retrieval of extended high dynamic range process in HDRI environment.
Abstract: The ability of agricultural and decorative plants to
absorb and detoxify TNT and RDX has been studied. All tested 8
plants, grown hydroponically, were able to absorb these explosives
from water solutions: Alfalfa > Soybean > Chickpea> Chikling vetch
>Ryegrass > Mung bean> China bean > Maize. Differently from
TNT, RDX did not exhibit negative influence on seed germination
and plant growth. Moreover, some plants, exposed to RDX
containing solution were increased in their biomass by 20%. Study of
the fate of absorbed [1-14ðí]-TNT revealed the label distribution in
low and high-molecular mass compounds, both in roots and above
ground parts of plants, prevailing in the later. Content of 14ðí in lowmolecular
compounds in plant roots are much higher than in above
ground parts. On the contrary, high-molecular compounds are more
intensively labeled in aboveground parts of soybean. Most part (up to
70%) of metabolites of TNT, formed either by enzymatic reduction
or oxidation, is found in high molecular insoluble conjugates.
Activation of enzymes, responsible for reduction, oxidation and
conjugation of TNT, such as nitroreductase, peroxidase,
phenoloxidase and glutathione S-transferase has been demonstrated.
Among these enzymes, only nitroreductase was shown to be induced
in alfalfa, exposed to RDX. The increase in malate dehydrogenase
activities in plants, exposed to both explosives, indicates
intensification of Tricarboxylic Acid Cycle, that generates reduced
equivalents of NAD(P)H, necessary for functioning of the
nitroreductase. The hypothetic scheme of TNT metabolism in plants
is proposed.
Abstract: Sonogram images of normal and lymphocyte thyroid tissues have considerable overlap which makes it difficult to interpret and distinguish. Classification from sonogram images of thyroid gland is tackled in semiautomatic way. While making manual diagnosis from images, some relevant information need not to be recognized by human visual system. Quantitative image analysis could be helpful to manual diagnostic process so far done by physician. Two classes are considered: normal tissue and chronic lymphocyte thyroid (Hashimoto's Thyroid). Data structure is analyzed using K-nearest-neighbors classification. This paper is mentioned that unlike the wavelet sub bands' energy, histograms and Haralick features are not appropriate to distinguish between normal tissue and Hashimoto's thyroid.
Abstract: In this paper, we propose use of convolutional codes
for file dispersal. The proposed method is comparable in complexity
to the information Dispersal Algorithm proposed by M.Rabin and for
particular choices of (non-binary) convolutional codes, is almost as
efficient as that algorithm in terms of controlling expansion in the
total storage. Further, our proposed dispersal method allows string
search.
Abstract: In recent years, it has been proposed security
architecture for sensor network.[2][4]. One of these, TinySec by Chris
Kalof, Naveen Sastry, David Wagner had proposed Link layer security
architecture, considering some problems of sensor network. (i.e :
energy, bandwidth, computation capability,etc). The TinySec employs
CBC_mode of encryption and CBC-MAC for authentication based on
SkipJack Block Cipher. Currently, This TinySec is incorporated in the
TinyOS for sensor network security.
This paper introduces TinyHash based on general hash algorithm.
TinyHash is the module in order to replace parts of authentication and
integrity in the TinySec. it implies that apply hash algorithm on
TinySec architecture. For compatibility about TinySec, Components
in TinyHash is constructed as similar structure of TinySec. And
TinyHash implements the HMAC component for authentication and
the Digest component for integrity of messages. Additionally, we
define the some interfaces for service associated with hash algorithm.
Abstract: The aim of the study was to investigate the possible
use of commercial Computational Fluid Dynamics (CFD) software in
the design process of a domestic gas boiler. Because of the limited
computational resources some simplifications had to be made in
order to contribute to the design in a reasonable timescale.
The porous media model was used in order to simulate the
influence of the pressure drop characteristic of particular elements of
a heat transfer system on the water-flow distribution in the system.
Further, a combination of CFD analyses and spread sheet
calculations was used in order to solve the flow distribution problem.