Abstract: Wireless Sensor Networks can be used to monitor the
physical phenomenon in such areas where human approach is nearly
impossible. Hence the limited power supply is the major constraint of
the WSNs due to the use of non-rechargeable batteries in sensor
nodes. A lot of researches are going on to reduce the energy
consumption of sensor nodes. Energy map can be used with
clustering, data dissemination and routing techniques to reduce the
power consumption of WSNs. Energy map can also be used to know
which part of the network is going to fail in near future. In this paper,
Energy map is constructed using the prediction based approach.
Adaptive alpha GM(1,1) model is used as the prediction model.
GM(1,1) is being used worldwide in many applications for predicting
future values of time series using some past values due to its high
computational efficiency and accuracy.
Abstract: The purposes of this study are 1) to study the frequent
English writing errors of students registering the course: Reading and
Writing English for Academic Purposes II, and 2) to find out the
results of writing error correction by using coded indirect corrective
feedback and writing error treatments. Samples include 28 2nd year
English Major students, Faculty of Education, Suan Sunandha
Rajabhat University. Tool for experimental study includes the lesson
plan of the course; Reading and Writing English for Academic
Purposes II, and tool for data collection includes 4 writing tests of
short texts. The research findings disclose that frequent English
writing errors found in this course comprise 7 types of grammatical
errors, namely Fragment sentence, Subject-verb agreement, Wrong
form of verb tense, Singular or plural noun endings, Run-ons
sentence, Wrong form of verb pattern and Lack of parallel structure.
Moreover, it is found that the results of writing error correction by
using coded indirect corrective feedback and error treatment reveal
the overall reduction of the frequent English writing errors and the
increase of students’ achievement in the writing of short texts with
the significance at .05.
Abstract: In this paper a new approach to face recognition is presented that achieves double dimension reduction making the system computationally efficient with better recognition results. In pattern recognition techniques, discriminative information of image increases with increase in resolution to a certain extent, consequently face recognition results improve with increase in face image resolution and levels off when arriving at a certain resolution level. In the proposed model of face recognition, first image decimation algorithm is applied on face image for dimension reduction to a certain resolution level which provides best recognition results. Due to better computational speed and feature extraction potential of Discrete Cosine Transform (DCT) it is applied on face image. A subset of coefficients of DCT from low to mid frequencies that represent the face adequately and provides best recognition results is retained. A trade of between decimation factor, number of DCT coefficients retained and recognition rate with minimum computation is obtained. Preprocessing of the image is carried out to increase its robustness against variations in poses and illumination level. This new model has been tested on different databases which include ORL database, Yale database and a color database. The proposed technique has performed much better compared to other techniques. The significance of the model is two fold: (1) dimension reduction up to an effective and suitable face image resolution (2) appropriate DCT coefficients are retained to achieve best recognition results with varying image poses, intensity and illumination level.
Abstract: Most of the losses in a power system relate to
the distribution sector which always has been considered.
From the important factors which contribute to increase losses
in the distribution system is the existence of radioactive flows.
The most common way to compensate the radioactive power
in the system is the power to use parallel capacitors. In
addition to reducing the losses, the advantages of capacitor
placement are the reduction of the losses in the release peak of
network capacity and improving the voltage profile. The point
which should be considered in capacitor placement is the
optimal placement and specification of the amount of the
capacitor in order to maximize the advantages of capacitor
placement.
In this paper, a new technique has been offered for the
placement and the specification of the amount of the constant
capacitors in the radius distribution network on the basis of
Genetic Algorithm (GA). The existing optimal methods for
capacitor placement are mostly including those which reduce
the losses and voltage profile simultaneously. But the
retaliation cost and load changes have not been considered as
influential UN the target function .In this article, a holistic
approach has been considered for the optimal response to this
problem which includes all the parameters in the distribution
network: The price of the phase voltage and load changes. So,
a vast inquiry is required for all the possible responses. So, in
this article, we use Genetic Algorithm (GA) as the most
powerful method for optimal inquiry.
Abstract: Hydrogen is considered to be the most promising
candidate as a future energy carrier. One of the most used
technologies for the electrolytic hydrogen production is alkaline
water electrolysis. However, due to the high energy requirements, the
cost of hydrogen produced in such a way is high. In continuous
search to improve this process using advanced electrocatalytic
materials for the hydrogen evolution reaction (HER), Ni type Raney
and macro-porous Ni-Co electrodes were prepared on AISI 304
stainless steel substrates by electrodeposition. The developed
electrodes were characterized by SEM and confocal laser scanning
microscopy. HER on these electrodes was evaluated in 30 wt.% KOH
solution by means of hydrogen discharge curves and galvanostatic
tests. Results show that the developed electrodes present a most
efficient behaviour for HER when comparing with the smooth Ni
cathode. It has been reported a reduction in the energy consumption
of the electrolysis cell of about 25% by using the developed coatings
as cathodes.
Abstract: In view of geological origin, formation of the shallow
gas reservoir of the Hangzhou Bay, northern Zhejiang Province,
eastern China, and original occurrence characteristics of the gassy
sand are analyzed. Generally, gassy sand in scale gas reservoirs is in
the state of residual moisture content and the approximate scope of
initial matric suction of sand ranges about from 0kPa to100kPa.
Results based on GDS triaxial tests show that the classical shear
strength formulas of unsaturated soil can not effectively describe basic
strength characteristics of gassy sand; the relationship between
apparent cohesion and matric suction of gassy sand agrees well with
the power function, which can reasonably be used to describe the
strength of gassy sand. In the stress path of gas release, shear strength
of gassy sand will increase and experimental results show the formula
proposed in this paper can effectively predict the strength increment.
When saturated strength indexes of the sand are used in engineering
design, moderate reduction should be considered.
Abstract: The present work was conducted for the synthesis of
nano size zerovalent iron (nZVI) and hexavalent chromium (Cr(VI))
removal as a highly toxic pollutant by using this nanoparticles. Batch
experiments were performed to investigate the effects of Cr(VI),
nZVI concentration, pH of solution and contact time variation on
the removal efficiency of Cr(VI). nZVI was synthesized by
reduction of ferric chloride using sodium borohydrid. SEM and
XRD examinations applied for determination of particle size and
characterization of produced nanoparticles. The results showed that
the removal efficiency decreased with Cr(VI) concentration and pH
of solution and increased with adsorbent dosage and contact time.
The Langmuir and Freundlich isotherm models were used for the
adsorption equilibrium data and the Langmuir isotherm model was
well fitted. Nanoparticle ZVI presented an outstanding ability to
remove Cr(VI) due to high surface area, low particle size and high
inherent activity.
Abstract: To study the performance of soybean (Glycine max L.) cultivars in varying weeding regimes, a field experiment was conducted in 2010. The experiment was split plot in a randomized complete block design with 3 replicates. The four cultivars and two lines of soybean including: Sahar, Hill, Sari, Telar, 032 and 033 in main plot and weeding regime consist of no weeding (control), one weeding (35 days after planting) and two weeding (35+20 days after planting) were randomized in sub plot. In weed infested plots inevitably had the highest yield reduction in all varieties. On the other hand, plots weeded twice showed the best performance for all cultivars and lines. Although 033 had the highest yield over weeding regimes, but Hill was the best cultivar in suppression of weeds, which indicated the competitiveness of this cultivar. Double weeding, with the use of competitive soybean cultivars would be an effective approach for producing yield.
Abstract: A comparative evaluation of acute toxicity of
synthesized nano silvers using two different procedures (biological
and chemical reduction methods) and silver ions on bacteria
Vibrio fischeri was investigated. The bacterial light inhibition test as
a toxicological endpoint was used by applying of a homemade
luminometer. To compare the toxicity effects as a quantitative
parameter, a nominal effective concentrations (EC) of chemicals and
a susceptibility constant (Z-value) of bacteria, after 5 min and 30 min
exposure times, were calculated. After 5 and 30 min contact times,
the EC50 values of two silver nanoparticles and the EC20 values were
about similar. It demonstrates that toxicity of silvers was independent
of their procedure. The EC values of nanoparticles were larger than
those of the silver ions. The susceptibilities(Z- Values) of V.fischeri
(L/mg) to the silver ions were greater than those of the nano silvers.
According to the EC and Z values, the toxicity of silvers decreased in
the following order: Silver ions >> silver nanoparticles from
chemical reduction method ~ silver nanoparticles from biological
method.
Abstract: In this paper, an erosion-based model for abrasive
waterjet (AWJ) turning process is presented. By using modified
Hashish erosion model, the volume of material removed by impacting
of abrasive particles to surface of the rotating cylindrical specimen is
estimated and radius reduction at each rotation is calculated.
Different to previous works, the proposed model considers the
continuous change in local impact angle due to change in workpiece
diameter, axial traverse rate of the jet, the abrasive particle roundness
and density. The accuracy of the proposed model is examined by
experimental tests under various traverse rates. The final diameters
estimated by the proposed model are in good accordance with
experiments.
Abstract: This paper presents a new method which applies an
artificial bee colony algorithm (ABC) for capacitor placement in
distribution systems with an objective of improving the voltage profile
and reduction of power loss. The ABC algorithm is a new population
based meta heuristic approach inspired by intelligent foraging behavior
of honeybee swarm. The advantage of ABC algorithm is that
it does not require external parameters such as cross over rate and
mutation rate as in case of genetic algorithm and differential evolution
and it is hard to determine these parameters in prior. The other
advantage is that the global search ability in the algorithm is implemented
by introducing neighborhood source production mechanism
which is a similar to mutation process. To demonstrate the validity
of the proposed algorithm, computer simulations are carried out on
69-bus system and compared the results with the other approach
available in the literature. The proposed method has outperformed the
other methods in terms of the quality of solution and computational
efficiency.
Abstract: The effect of dry milling on the carbothermic
reduction of celestite was investigated. Mixtures of celestite
concentrate (98% SrSO4) and activated carbon (99% carbon) was
milled for 1 and 24 hours in a planetary ball mill. Un-milled and
milled mixtures and their products after carbothermic reduction were
studied by a combination of XRD and TGA/DTA experiments. The
thermogravimetric analyses and XRD results showed that by milling
celestite-carbon mixtures for one hour, the formation temperature of
strontium sulfide decreased from about 720°C (in un-milled sample)
to about 600°C, after 24 hours milling it decreased to 530°C. It was
concluded that milling induces increasingly thorough mixing of the
reactants to reduction occurring at lower temperatures
Abstract: Since dealing with high dimensional data is
computationally complex and sometimes even intractable, recently
several feature reductions methods have been developed to reduce
the dimensionality of the data in order to simplify the calculation
analysis in various applications such as text categorization, signal
processing, image retrieval, gene expressions and etc. Among feature
reduction techniques, feature selection is one the most popular
methods due to the preservation of the original features.
In this paper, we propose a new unsupervised feature selection
method which will remove redundant features from the original
feature space by the use of probability density functions of various
features. To show the effectiveness of the proposed method, popular
feature selection methods have been implemented and compared.
Experimental results on the several datasets derived from UCI
repository database, illustrate the effectiveness of our proposed
methods in comparison with the other compared methods in terms of
both classification accuracy and the number of selected features.
Abstract: This research studied recycled waste by the Recyclable Material Bank Project of 4 universities in the central region of Thailand for the evaluation of reducing greenhouse gas emissions compared with landfilling activity during July 2012 to June 2013. The results showed that the projects collected total amount of recyclable wastes of about 911,984.80 kilograms. Office paper had the largest amount among these recycled wastes (50.68% of total recycled waste). Groups of recycled waste can be prioritized from high to low according to their amount as paper, plastic, glass, mixed recyclables, and metal, respectively. The project reduced greenhouse gas emissions equivalent to about 2814.969 metric tons of carbon dioxide. The most significant recycled waste that affects the reduction of greenhouse gas emissions is office paper which is 70.16% of total reduced greenhouse gasses emission. According to amount of reduced greenhouse gasses emission, groups of recycled waste can be prioritized from high to low significances as paper, plastic, metals, mixed recyclables, and glass, respectively.
Abstract: Selected Mapping (SLM) is a PAPR reduction technique, which converts the OFDM signal into several independent signals by multiplication with the phase sequence set and transmits one of the signals with lowest PAPR. But it requires the index of the selected signal i.e. side information (SI) to be transmitted with each OFDM symbol. The PAPR reduction capability of the SLM scheme depends on the selection of phase sequence set. In this paper, we have proposed a new phase sequence set generation scheme based on M-ary chaotic sequence and a mapping scheme to map quaternary data to concentric circle constellation (CCC) is used. It is shown that this method does not require SI and provides better SER performance with good PAPR reduction capability as compared to existing SLMOFDM methods.
Abstract: The H.264/AVC video coding standard contains a number of advanced features. Ones of the new features introduced in this standard is the multiple intramode prediction. Its function exploits directional spatial correlation with adjacent block for intra prediction. With this new features, intra coding of H.264/AVC offers a considerably higher improvement in coding efficiency compared to other compression standard, but computational complexity is increased significantly when brut force rate distortion optimization (RDO) algorithm is used. In this paper, we propose a new fast intra prediction mode decision method for the complexity reduction of H.264 video coding. for luma intra prediction, the proposed method consists of two step: in the first step, we make the RDO for four mode of intra 4x4 block, based the distribution of RDO cost of those modes and the idea that the fort correlation with adjacent mode, we select the best mode of intra 4x4 block. In the second step, we based the fact that the dominating direction of a smaller block is similar to that of bigger block, the candidate modes of 8x8 blocks and 16x16 macroblocks are determined. So, in case of chroma intra prediction, the variance of the chroma pixel values is much smaller than that of luma ones, since our proposed uses only the mode DC. Experimental results show that the new fast intra mode decision algorithm increases the speed of intra coding significantly with negligible loss of PSNR.
Abstract: This paper presents the results related to the
interference reduction technique in multistage multiuser detector for
asynchronous DS-CDMA system. To meet the real-time
requirements for asynchronous multiuser detection, a bit streaming,
cascade architecture is used. An asynchronous multiuser detection
involves block-based computations and matrix inversions. The paper
covers iterative-based suboptimal schemes that have been studied to
decrease the computational complexity, eliminate the need for matrix
inversions, decreases the execution time, reduces the memory
requirements and uses joint estimation and detection process that
gives better performance than the independent parameter estimation
method. The stages of the iteration use cascaded and bits processed
in a streaming fashion. The simulation has been carried out for
asynchronous DS-CDMA system by varying one parameter, i.e.,
number of users. The simulation result exhibits that system gives
optimum bit error rate (BER) at 3rd stage for 15-users.
Abstract: This paper emphasizes on the application of genetic algorithm (GA) to optimize the parameters of the TMD for achieving the best results in the reduction of the building response under earthquake excitations. The Integral of the Time multiplied Absolute value of the Error (ITAE) based on relative displacement of all floors in the building is taken as a performance index of the optimization criterion. The problem of robustly TMD controller design is formatted as an optimization problem based on the ITAE performance index to be solved using GA that has a story ability to find the most optimistic results. An 11–story realistic building, located in the city of Rasht, Iran is considered as a test system to demonstrate effectiveness of the proposed GA based TMD (GATMD) controller without specifying which mode should be controlled. The results of the proposed GATMD controller are compared with the uncontrolled structure through timedomain simulation and some performance indices. The results analysis reveals that the designed GA based TMD controller has an excellent capability in reduction of the seismically excited example building and the ITAE performance, that is so for remains as unknown, can be introduced a new criteria - method for structural dynamic design.
Abstract: Different techniques for estimating seasonal water
use from soil profile water depletion frequently do not account for
flux below the root zone. Shallow water table contribution to supply
crop water use may be important in arid and semi-arid regions.
Development of predictive root uptake models, under influence of
shallow water table makes it possible for planners to incorporate
interaction between water table and root zone into design of irrigation
projects. A model for obtaining soil moisture depletion from root
zone and water movement below it is discussed with the objective to
determine impact of shallow water table on seasonal moisture
depletion patterns under water table depth variation, up to the bottom
of root zone. The role of different boundary conditions has also been
considered. Three crops: Wheat (Triticum aestivum), Corn (Zea
mays) and Potato (Solanum tuberosum), common in arid & semi-arid
regions, are chosen for the study. Using experimentally obtained soil
moisture depletion values for potential soil moisture conditions,
moisture depletion patterns using a non linear root uptake model have
been obtained for different water table depths. Comparative analysis
of the moisture depletion patterns under these conditions show a wide
difference in percent depletion from different layers of root zone
particularly top and bottom layers with middle layers showing
insignificant variation in moisture depletion values. Moisture
depletion in top layer, when the water table rises to root zone
increases by 19.7%, 22.9% & 28.2%, whereas decrease in bottom
layer is 68.8%, 61.6% & 64.9% in case of wheat, corn & potato
respectively. The paper also discusses the causes and consequences
of increase in moisture depletion from top layers and exceptionally
high reduction in bottom layer, and the possible remedies for the
same. The numerical model developed for the study can be used to
help formulating irrigation strategies for areas where shallow
groundwater of questionable quality is an option for crop production.
Abstract: We constructed a method of noise reduction for
JPEG-compressed image based on Bayesian inference using the
maximizer of the posterior marginal (MPM) estimate. In this method,
we tried the MPM estimate using two kinds of likelihood, both of
which enhance grayscale images converted into the JPEG-compressed
image through the lossy JPEG image compression. One is the
deterministic model of the likelihood and the other is the probabilistic
one expressed by the Gaussian distribution. Then, using the Monte
Carlo simulation for grayscale images, such as the 256-grayscale
standard image “Lena" with 256 × 256 pixels, we examined the
performance of the MPM estimate based on the performance measure
using the mean square error. We clarified that the MPM estimate via
the Gaussian probabilistic model of the likelihood is effective for
reducing noises, such as the blocking artifacts and the mosquito noise,
if we set parameters appropriately. On the other hand, we found that
the MPM estimate via the deterministic model of the likelihood is not
effective for noise reduction due to the low acceptance ratio of the
Metropolis algorithm.